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Threatened primates experience high human densities: Adding an index of threat to the IUCN Red List criteria


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IUCN Red List conservation status is apparently judged mainly by assessment of species' susceptibility to threat. However, risk must often depend also on the threat itself. Therefore, we investigate the value of adding to IUCN's current criteria a separate index of threat, human density. Human density in the geographic range of Threatened primate species is significantly higher than in the range of Lower Risk species. Thus, Threatened species are both susceptible, and experience more threat. However, the match is far from perfect. Given abundant other evidence of adverse effects of high human density, the mismatch emphasizes the potential benefit of adding an index of threat to the current criteria. A main advantage might be improved assessment, given the amount of up-to-date data on threats compared with the paucity on reactions to threat. The simplest means of incorporation might be to increase the status of species that experience higher than a certain threshold human density.
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Threatened primates experience high human densities: adding an
index of threat to the IUCN Red List criteria
A.H. Harcourt*, S.A. Parks
Department of Anthropology, University of California, One Shields Avenue, Davis, CA 95616, USA
Received 26 March 2001; received in revised form 15 December 2001; accepted 17 April 2002
IUCN Red List conservation status is apparently judged mainly by assessment of species’ susceptibility to threat. However, risk
must often depend also on the threat itself. Therefore, we investigate the value of adding to IUCN’s current criteria a separate index
of threat, human density. Human density in the geographic range of Threatened primate species is significantly higher than in the
range of Lower Risk species. Thus, Threatened species are both susceptible, and experience more threat. However, the match is far
from perfect. Given abundant other evidence of adverse effects of high human density, the mismatch emphasizes the potential
benefit of adding an index of threat to the current criteria. A main advantage might be improved assessment, given the amount of
up-to-date data on threats compared with the paucity on reactions to threat. The simplest means of incorporation might be to
increase the status of species that experience higher than a certain threshold human density. #2002 Elsevier Science Ltd. All rights
Keywords: Conservation; Human density; IUCN; Primates; Red List
1. Introduction
IUCN currently uses for its influential Red List of
threatened species three main indices to determine the
conservation status of a species (IUCN, 1996, 2000).
These indices are, broadly, the species’ population size,
rate of population decline, and its geographic range. The
fourth index, a population viability analysis, is hardly
used at all. If any one of the indices indicates that a spe-
cies crosses a threshold (below a certain population size
or geographic range, above a certain rate of decline), the
species is given the relevant higher conservation status
(from Lower Risk to Vulnerable to Endangered to Cri-
tically Endangered; IUCN, 1996, 2000).
These indices assess, in effect, the species’ predisposi-
tion to threat, and their reaction to it. That is entirely
appropriate, because species react differently to the
same threat (Brown, 1971; Terborgh, 1974; Diamond,
1984; Jablonski, 1991; Laurance, 1991; Leach and
Givnish, 1996; Harcourt, 1998; Jernvall and Wright,
1998; Cowlishaw and Dunbar, 2000; Harcourt, 2001).
However, estimates of relative probability of extinction,
which is essentially what the Red List classifications are,
depend not just on the species’ susceptibility to threat,
but also on the nature and intensity of the threat itself.
The crucial distinction between susceptibility to threat
and intensity of threat is one that is hidden not only by
the current Red List criteria, but perhaps also by the use
of the word ‘threatened’ which can mean both ‘suscep-
tible’ and ‘under threat’. An open house is susceptible to
burglary, but it is not threatened by it unless a burglar is
in the vicinity. Thus, a species becomes more threatened
as soon as a large, polluting city is built next to its
range, even if population size, rate of decline, and geo-
graphic range all remain the same. That is why analyses
showing that hotspots of biodiversity are also hotspots
of human activity are so alarming (Dobson et al., 1997;
Cincotta et al., 2000; Balmford et al., 2001).
The performance of the IUCN Red List criteria are
continuously evaluated both within IUCN (Hilton-
Taylor, 2000) and outside (Akc¸ akaya et al., 2000). Here
we add to those evaluations by proposing that several
advantages would accrue if an index of threat were
explicitly incorporated as an additional major criterion
to categorize the conservation status of species.
0006-3207/02/$ - see front matter #2002 Elsevier Science Ltd. All rights reserved.
PII: S0006-3207(02)00146-5
Biological Conservation 109 (2003) 137–149
* Corresponding author.
E-mail address: (A.H. Harcourt).
First, an additional separate, explicit criterion, espe-
cially one for which abundant evidence indicates its
relevance, should improve assessment of risk, because it
could provide an extra indicator of risk that is not
necessarily always used in the current criteria.
Second, increased transparency is a goal of the Red
List changes (Hilton-Taylor, 2000). Adding threat as a
separate criterion should make explicit what might be
a fairly cryptic index already sometimes used. Measures
of threat in the form of ‘levels of exploitation’, and ‘the
effects of introduced taxa, hybridization, pathogens,
pollutants, competitors, or parasites’ are currently listed
as potential measures to predict future population
decline (IUCN, 1996, 2000). However, intensity of any
threat itself is not a separate criterion in the Red List’s
assessment of conservation status (IUCN, 1996, 2000).
Thus its incorporation into assessment of status is both
presumably irregular, and also hidden to the user.
Third, if a species’ conservation status was explicitly
indicated as due to threat, as opposed to reaction to
threat, management might be better refined. The Red
Lists are produced to focus attention on especially
threatened species and to help prioritization of action
(Mace, 1995; IUCN, 2000). Management decisions
could be very different depending on whether the threat
itself, or the species’ response to the threat, is judged to
be the prime danger. If threat is the main problem, the
threat needs mitigation (e.g. prevent settlement around
the forest); if susceptibility is the main problem, we
mitigate that (e.g. translocate individuals to increase
genetic heterogeneity).
Fourth, conservation status is best assessed with
good, abundant, up-to-date, easily obtainable data
(Gaston, 1994, p. 144). Data on human activity are such
(e.g. World Resources Institute, 2000). By contrast, data
on population size and rate of population decline are
usually little more than informed guesswork, especially
in tropical countries (Harcourt, 1995).
A specific index of threat needs to be chosen. Abun-
dant evidence indicates that across continents, rates of
disappearance of habitat and of species correlate with
human density, or other measures of human activity
(Parker and Graham, 1989; Barnes, 1990; Hannah et
al., 1994; Kerr and Currie, 1995; McNeely et al., 1995;
Harcourt, 1996; Bawa and Dayanandan, 1997; Hoare
and Du Toit, 1999; Muchaal and Ngandjui, 1999;
Robinson et al., 1999; Cowlishaw and Dunbar, 2000,
Chapter 8; Woodroffe, 2000; McKinney, 2001). Also
up-to-date, precise data on human density are easily
available (e.g. World Resources Institute, 2000). We
therefore suggest that human density as an index of
threat might be a good candidate criterion to use as an
additional measure for assessing a species’ conservation
We here test the value of adding threat in the form of
human density as a criterion by calculating mean
human density in the geographic range of all primate
species, one of the better known orders of mammal, and
comparing it with the species’ 1996 Red List conserva-
tion status. The predictions are that (1) Threatened
species experience a higher human density in their geo-
graphic range than do the Lower Risk species (Wright
and Jernvall, 1999); and that (2) the most threatened
species will experience the highest human density.
Additionally, we assess conservation status on the basis
of only the two measures for which most data are
available, geographic range of species, and human den-
sity within the range. The null hypothesis is that threat
is well incorporated into the current listing, and thus
that the new listing will match the current Red List. If
the new list shows a change in conservation status of
many species, the value of the Red List probably needs
2. Methods
We used the IUCN Red List (IUCN, 1996) to sepa-
rate taxa according to their conservation status. [We did
not use the latest listing (IUCN, 2000), because its tax-
onomy is too new for adequate assessment.] The status
of each species was then related to human density. As in
all such analyses, circularity is a potential problem if the
correlate tested was explicitly used in the assessment of
conservation status in the first place. We cannot know
whether it was for Red List categorizations, because so
few of the IUCN Red List assessments are published,
and the unpublished ones are so difficult to obtain.
Previous detailed IUCN Red List assessments for pri-
mates have been produced, but they were published
before the current quantitative criteria were finalized
(Lee et al., 1988; Harcourt and Thornback, 1990).
Geographic range as used by IUCN probably includes
an element of human influence, but how much, we do
not know. With so little indication of whether or how
human density was used in assessing status in the cur-
rent Red List, we consider that it is valid to test human
density as a potentially useful additional index of con-
servation status.
Analyses were performed for the globe, and then for
the continents separately, because continents differ so
greatly in their proportions of threatened species
and their human density, as well as in many other
aspects of their natural and human geography (World
Resources Institute, 2000).
2.1. Conservation status
IUCN now has five main categories of conservation
status (IUCN, 2000), three threatened categories—
Critically Endangered, Endangered, Vulnerable—and
two Lower Risk categories, Near Threatened and Least
138 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
Concern. We combine these two safer categories into
one, Lower Risk.
2.2. Taxonomy
Taxonomic nomenclature and listing is mostly from
Groves (1993), Corbet and Hill (1991), and the Red List
(IUCN, 1996). Where the sources differed, the one with
the fewer species was chosen, although Papio remains as
five species. Callicebus is treated as three species (as in
Wolfheim 1983), because the two main authorities differ
(Hershkovitz, 1990; Groves, 1993). Not all taxa in the
Red List (IUCN, 1996) were included in the analysis
here. Missing species are those that do not appear in
one or other of the two main taxonomic sources. The
missing species are largely recent splits reflecting minor
morphological variations at single geographic sites,
some of which are taxonomically contested. The exclu-
sion of the 1996 IUCN Red List species in no instance
affects the Red List classification of their sister species,
because the geographic ranges of the excluded species
are very small by comparison with their sister species’
ranges. Brachyteles is the one exception: the split species
each have about the same size of geographic range.
However, the original single species is as threatened as
either of the Red List’s two species. The 1996 Red
List species not included in this analysis are, in order of
listing, Aotus brumbacki, A. lemurinus, Brachyteles
hypoxanthus, Callicebus dubius, Cebus kaapori, Cebus
xanthosternos, Cercopithecus preussi, Cercopithecus
sclateri, Cercopithecus solatus, Hapalemur aureus,
Macaca brunnescens, Macaca pagensis, Microcebus
myoxinus, Saimiri oerstedii (possibly a human introduc-
tion), Saimiri vanzolinii, Trachypithecus delacouri, and
Trachypithecus poliocephalus.
2.3. Geographic range
We took species’ geographic range from, in effect,
convex polygon coverages digitized from maps in
Wolfheim (1983), with subsequent correction and addi-
tion from, in particular, Corbet and Hill (1992), Groves
(1993), Niemitz (1984), Hershkovitz (1987a, b; 1990),
Lernould (1988), Nash et al., (1989), Harcourt and
Thornback (1990), Rylands et al. (1993), Ford (1994),
Mittermeier et al. (1994), Oates et al. (1994), and Kinzey
(1997). The coverages produce maximum ranges, and
thus minimize recent retreats of range due to humans.
2.4. Human density
Human density data were taken from the CIESIN
web site (Tobler et al., 1995). These density data are far
more precise than in most other such global analyses,
which often use countrywide means as the data (e.g.
Kerr and Currie, 1995; McKinney, 2001). The data are
presented in the site as a grid with a cell size of
0.0830.083 degrees (or 5050, or approximately 9
km9 km at the equator). We used the ‘smoothed’ ver-
sion of the data in the site, because it removes abrupt
transitions in density at political boundaries, and thus
provides a more realistic distribution of densities.
From the data, we calculated the mean density in each
species’ geographic range by use of Arc/Info (ESRI Inc.,
1998a) and ArcView GIS (ESRI Inc., 1998b). Each
species’ geographic range was converted to a grid/raster
format using ArcView GIS. The ‘con’ functions in Arc/
Info ‘clipped’ the human density that overlapped the
particular geographic range of a species. The mean
value of such overlapping human density values was
used in this paper.
Means are affected by extremes, of course. However,
we suggest that a species’ range that is mostly empty of
humans, but has a city at one edge, is better represented
by a density value that incorporates that city than one
that does not, such as the mode or median.
2.5. Statistics and independence of data
Statistical tests require independence of data. Given
that certain sorts of organism are inherently more prone
to extinction than are others (earlier), species might not
be independent data points: if one species in a genus or
family is Threatened, the others might be more likely to
be also. Furthermore, neither species, nor human den-
sities are equally distributed across the globe. Therefore,
phylogeny is confounded with human density. Asia, for
instance, has an overall human density about five times
that of the other continents ((World Resources Insti-
tute, 1998). Thus, all five of the purely Asian snub-
nosed langur species [Pygathrix (Rhinopithecus)] are not
only Threatened but also in regions of relatively high
human density (147 people/km
), whereas all five
baboon species of Africa (Papio) are both Low Risk and
in relatively low density (median of 26 people/km
Therefore, in addition to analysis with species as data
points, we also take account of phylogeny by use of
Comparative Analysis by Independent Contrasts
(CAIC) (Purvis and Rambaut, 1995), and we examine
the continents separately. For this analysis, the phylo-
geny used is that of Purvis and Webster (1999), which is
an update from the phylogeny of Purvis (1995), perhaps
the most broadly substantiated single phylogeny for all
primates so far published.
These means of accounting for dependence still do not
get over the problem that several species can overlay a
region with a single human density. However, (1) unless
overlap of geographic range is complete, two species
have the chance to experience different mean densities in
their range; (2) as species can react differently to the
same threat, even if the overlap is complete, the two
species could have a different conservation status.
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 139
Statistical tests are performed with JMP (SAS Insti-
tute Inc, 1995), and with Statview SE+ (Abacus Con-
cepts, 1990–1991) for the Wilcoxon matched pairs,
signed rank tests. All probabilities are two-tailed.
3. Results
3.1. Human density in relation to Red List conservation
The current IUCN criteria apply to all taxa and all
continents. Globally, human density is higher in the
geographic ranges of Threatened species than it is in
the ranges of Lower Risk species, differing significantly
across the four IUCN classes of conservation status
(F=9.15; df=3; P<0.0001) (Table 1; Fig. 1). While
human density does not differ across the three classes of
Threatened status (F=0.92, df=2), the human density
of each threatened status class independently differs
significantly from that of Low Risk species (N=45, 22,
9 vs. 127; df=1; F>7.0; P<0.01). Combining the three
Threatened classes, human density in the geographic
ranges of Threatened species (56 people/km
) is sig-
nificantly greater (F=25.65; df=1; P<0.0001) than
that in the geographic ranges of Lower Risk species (21
) (Table 2, Fig. 2). Thus the first prediction
that threatened species will experience higher human
density than unthreatened is upheld. However, the sec-
ond, that degree of threat would be proportional to
human density, is not.
A very strong continental effect exists in this global
comparison of densities, indeed a stronger effect than of
conservation status, whether four, three, or two levels
of conservation status are analyzed (F>50.0,
P<0.0001). That is not surprising given the differences
between the continents in overall densities, and propor-
tions of Threatened species (Fig. 1). We nevertheless
lump the continents in the global comparisons, because
that is how IUCN currently produces its Red Lists.
Accounting for phylogeny by use of CAIC (Methods),
the difference is upheld. With 200 species available for
comparison, 50 contrasts between phylogenetically
independent taxa with different conservation status
indicate that the more threatened taxa are significantly
likely to experience higher human density than are taxa
of lower conservation status (across the four categories,
32 of the 50 contrasts showed the more threatened
taxon with higher human density than the less threa-
tened taxon; N=32/18; T=356; z=2.72; P<0.01).
Comparing all Threatened with Low Risk (two cate-
gories, N=44 contrasts), the difference was even more
obvious (N=32/12; T=184; z=3.63; P<0.001). As in
the phylogenetically uncorrected analysis, no significant
differences existed within the Threatened classes
(N=16/9; T=118, z=1.2; P>0.1).
Taking the continents separately [significant hetero-
geneity exists among them (earlier)], human density
correlates significantly with conservation status in Asia
and in South and Central America, but not in Africa or
Madagascar (Table 2, Fig. 1). However in no continent
alone are the differences significant when phylogeny is
accounted for (P>0.1).
IUCN (1996) lists nine primate species as Data Defi-
cient, all in Asia. [By 2000, over twice as many were so
listed, over two thirds of them in Asia (IUCN, 2000).
Many of these were not included in this analysis, for the
reasons stated in Section 2.] Data Deficient species are
not assigned a threat status. If the median human den-
sity of 56 people/km
for Threatened species is taken as
a threshold, and taxa above that threshold classified as
Threatened, five of the nine Data Deficient species
should be classified as Threatened. In other words, use
of human density as a criterion allows the Red List to
provide a warning that otherwise would be missing.
3.2. The distribution of status in relation to human
So far we have analyzed human density in relation to
Red List status, asking whether taxa with higher Red
List status experience higher human densities. They do.
Alternatively, we can ask about the distribution of taxa
of different Red List status in regions of differing
human density. To answer this question, we divided the
range of human densities per continent and globally
into five equal divisions, and examined the distribution
of species of different status across the divisions.
The results provide rather a different picture from the
previous analysis, although the same trend. A sub-
stantial majority of species on all continents except
Madagascar exist in the lowest quantile of human den-
sity (74% in Africa, 67% in Asia, 92% in the Americas,
33% in Madagascar, and 91% globally). In other
words, and not surprisingly, most taxa, including some
Critically Endangered taxa, occur in regions of low
human density—most primates are in forest, in which
humans tend not to be at high density.
A methodological consequence of the fact that most
taxa are in this one category of lowest quantile of
human density is that there are not enough entries in the
other four quantiles to compare the distribution of all
four conservation categories across all five human den-
sity categories. We thus performed a 22w
on number
of Threatened compared with Lower Risk species in the
lowest density quantile compared with the rest. The
result is, as expected, a significantly greater proportion
of Threatened species in regions of higher human den-
sity than in regions of the lowest human density across
the globe and in the Americas, but not in the other
continents (Globe, w
=13.3, P<0.001; Americas,
=9.1, P<0.01; Africa, Asia, Madagascar, P>0.1).
140 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
Table 1
Per continent for each primate species for which data are available, their IUCN Red List conservation status (IUCN), mean human density in their
geographic range in people/km
(HD), the size of their geographic range in km
(GR) (or ‘extent of occurrence’; IUCN, 1996), and their new
conservation status with human density and geographic range alone used to classify status (New CS) (see Section 2 for details)
Allenopithecus nigroviridis 4 8.33 38.92 L
Arctocebus aureus 4 7.50 75.66 L
Arctocebus calabarensis 4* 142.23 23.54 H
Cercocebus agilis 4 9.52 101.31 L
Cercocebus galeritus 4 4.53 0.39 I
Cercocebus torquatus 4* 97.56 51.30 I
Cercopithecus ascanius 4 29.76 281.39 I
Cercopithecus campbelli 4* 61.06 52.03 I
Cercopithecus cephus 4 17.42 75.01 L
Cercopithecus diana 3* 58.36 32.04 H
Cercopithecus erythrogaster 3* 281.40 2.80 H*
Cercopithecus erythrotis 3* 134.41 8.55 H
Cercopithecus hamlyni 4* 43.92 26.04 H
Cercopithecus lhoesti 4* 66.09 38.75 I
Cercopithecus mitis 4* 32.39 418.12 I
Cercopithecus mona 4* 135.78 46.01 I
Cercopithecus neglectus 4 17.67 284.12 L
Cercopithecus nictitans 4* 44.99 161.99 I
Cercopithecus petaurista 4* 62.33 58.37 I
Cercopithecus pogonias 4 16.54 94.08 L
Cercopithecus wolfi 4 18.38 143.43 L
Chlorocebus aethiops 4 31.24 1439.37 I
Colobus angolensis 4 21.00 204.60 L
Colobus guereza 4* 38.30 236.60 I
Colobus polykomos 4* 33.51 47.80 I
Colobus satanas 3 9.01 28.77 I
Colobus vellerosus 3* 79.55 31.74 H
Erythrocebus patas 4 27.11 592.43 L
Euoticus elegantulus 4 8.25 72.96 L
Euoticus pallidus 4* 139.05 21.16 H
Galago alleni 4* 38.35 61.15 I
Galago gallarum 4 12.22 78.20 L
Galago matschiei 4* 104.30 19.18 H
Galago moholi 4 18.31 442.24 L
Galago senegalensis 4* 34.11 785.46 I
Galagoides demidoff 4* 35.36 435.48 I
Galagoides thomasi 4* 45.84 68.80 I
Galagoides zanzibaricus 4 30.43 117.17 I
Gorilla gorilla 2 15.81 80.86 L
Lophocebus albigena 4 16.25 170.33 L
Lophocebus aterrimus 4 13.77 96.53 L
Macaca sylvanus 3* 176.91 7.74 H
Mandrillus leucophaeus 2* 88.82 12.43 H
Mandrillus sphinx 4 11.30 42.84 L
Miopithecus talapoin 4 17.32 117.11 L
Otolemur crassicaudatus 4 27.07 418.06 L
Otolemur garnetti 4* 33.44 66.99 I
Pan paniscus 2 7.84 46.80 L
Pan troglodytes 2 29.11 249.80 I
Papio anubis 4* 34.18 806.91 I
Papio cynocephalus 4 20.97 379.97 L
Papio hamadryas 4 31.17 114.02 I
Papio papio 4 25.59 39.49 L
Papio ursinus 4 22.09 317.82 L
Perodicticus potto 4* 38.72 339.72 I
Procolobus badius 4* 38.03 226.14 I
Procolobus verus 4* 65.72 47.04 I
Theropithecus gelada 4* 104.74 12.49 H
(Table continued on next page)
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 141
Table 1 (continued)
Southeast Asia
Hylobates agilis 4 50.92 50.45 I
Hylobates concolor 2* 223.61 10.99 H
Hylobates gabriellae 4 94.48 27.66 H
Hylobates hoolock 4* 154.32 79.45 I
Hylobates klossii 3 56.80 0.91 H
Hylobates lar 4* 105.31 76.19 I
Hylobates leucogenys 4 46.54 17.22 H
Hylobates moloch 1* 990.71 5.39 H*
Hylobates muelleri 4 20.57 56.47 L
Hylobates pileatus 3 74.71 22.16 H
Hylobates syndactylus 4 77.56 20.37 H
Loris tardigradus 3* 311.32 81.32 I
Macaca arctoides 3* 156.48 172.65 I
Macaca assamensis 3* 144.73 156.69 I
Macaca cyclopis 3* 400.33 3.14 H*
Macaca fascicularis 4* 130.26 253.58 I
Macaca fuscata 2* 322.45 16.83 H
Macaca maura 2* 193.45 1.49 H*
Macaca mulatta 4* 236.81 577.84 I
Macaca nemestrina 3 81.31 312.69 I
Macaca nigra 2 52.30 1.69 H
Macaca ochreata 4 32.94 3.69 H
Macaca radiata 4* 287.97 70.82 I
Macaca silenus 2* 260.13 3.51 H*
Macaca sinica 4* 270.33 6.49 H
Macaca thibetana 4* 332.88 138.70 I
Macaca tonkeana 4 40.34 11.10 H
Nasalis larvatus 3 31.85 28.40 H
Nycticebus coucang 4* 113.73 375.82 I
Nycticebus pygmaeus 3* 122.25 45.92 I
Pongo pygmaeus 3 11.41 31.83 I
Presbytis comata 2* 928.97 4.79 H*
Presbytis frontata 4 22.37 25.77 I
Presbytis hosei 4 12.42 22.22 I
Presbytis melalophos 4 81.24 65.74 I
Presbytis potenziani 3 56.80 0.92 H
Presbytis rubicunda 4 15.86 65.42 L
Presbytis thomasi 4 59.17 5.07 H
Pygathrix avunculus 1* 147.44 1.13 H*
Pygathrix bieti 2 48.02 3.64 H
Pygathrix brelichi 2* 253.74 0.44 H*
Pygathrix nemaeus 2 82.92 41.57 I
Pygathrix roxellana 3* 163.63 2.48 H*
Semnopithecus entellus 4* 333.82 281.52 I
Simias concolor 2 56.80 0.92 H
Tarsius bancanus 4 104.27 34.54 H
Tarsius dianae 4 14.00 0.02 I
Tarsius spectrum 4 56.24 7.99 H
Tarsius syrichta 4* 148.42 6.47 H
Trachypithecus auratus 3* 848.30 13.03 H
Trachypithecus cristatus 4 84.88 123.43 I
Trachypithecus francoisi 3* 197.52 17.36 H
Trachypithecus geei 4 88.27 1.38 H*
Trachypithecus johnii 3* 327.42 2.43 H
Trachypithecus obscurus 4 88.37 23.51 H
Trachypithecus phayrei 4 103.62 123.93 I
Trachypithecus pileatus 3* 191.80 44.53 I
Trachypithecus vetulus 3* 309.73 4.73 H*
Allocebus trichotis 1 15.89 0.07 I
Avahi laniger 4* 27.20 9.30 I
142 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
Table 1 (continued)
Avahi occidentalis 3* 19.28 1.00 I
Cheirogaleus major 4* 25.61 12.04 I
Cheirogaleus medius 4 11.64 14.64 I
Daubentonia madagascariensis 2* 26.01 12.87 I
Eulemur coronatus 3 16.00 0.75 I
Eulemur fulvus 4 17.58 24.76 I
Eulemur macaco 3 14.47 1.00 I
Eulemur mongoz 3* 21.19 2.46 I
Eulemur rubriventer 3* 29.36 6.39 H
Hapalemur griseus 4* 28.77 13.29 I
Hapalemur simus 1* 41.10 0.07 H
Indri indri 2* 25.52 5.21 I
Lemur catta 3 11.88 12.30 I
Lepilemur dorsalis 3 16.68 0.65 I
Lepilemur edwardsi 4 9.56 5.42 I
Lepilemur leucopus 4 15.59 3.46 I
Lepilemur microdon 4* 23.96 4.08 I
Lepilemur mustelinus 4* 31.07 6.62 H
Lepilemur ruficaudatus 4 9.90 5.83 I
Lepilemur septentrionalis 3* 17.92 0.21 I
Microcebus murinus 4 11.07 17.21 I
Microcebus rufus 4* 28.63 13.65 I
Mirza coquereli 3 8.94 3.86 I
Phaner furcifer 4 8.71 4.35 I
Propithecus diadema 2* 27.98 7.28 I
Propithecus tattersalli 1 11.00 0.05 I
Propithecus verreauxi 3 10.78 20.34 I
Varecia variegata 2* 26.79 6.34 I
Alouatta belzebul 4* 5.43 174.00 L*
Alouatta caraya 4* 14.29 236.73 L
Alouatta fusca 3* 64.62 83.90 I
Alouatta palliata 4* 60.65 56.54 I
Alouatta pigra 4* 43.34 28.91 H
Alouatta seniculus 4* 11.05 579.75 L
Aotus azarae 4 3.72 56.58 L
Aotus infulatus 4 4.77 336.15 L*
Aotus miconax 3* 6.75 19.90 I
Aotus nancymae 4 0.62 27.09 I
Aotus nigriceps 4 2.01 121.64 L*
Aotus trivirgatus 4 2.09 83.73 L
Aotus vociferans 4* 20.71 199.31 L
Ateles belzebuth 3* 15.07 227.38 L
Ateles chamek 4 4.09 188.86 L*
Ateles fusciceps 3* 43.22 13.15 H
Ateles geoffroyi 4* 55.26 84.89 I
Ateles marginatus 2 4 36.91 L
Ateles paniscus 4 3.8 96.01 L
Brachyteles arachnoides 2* 86.99 43.09 I
Cacajao calvus 3 1.59 17.02 I
Cacajao melanocephalus 4 0.54 67.66 L
Callicebus moloch 4 2.81 405.50 L*
Callicebus personatus 3* 68.88 72.74 I
Callicebus torquatus 4 1.14 189.48 L*
Callimico goeldii 3 2.55 113.17 L
Callithrix argentata 4 3.81 111.42 L
Callithrix aurita 2* 142.62 17.35 H
Callithrix emiliae 4 1.41 21.41 I
Callithrix flaviceps 2* 52.08 4.32 H
Callithrix geoffroyi 3* 28.12 12.33 I
(Table continued on next page)
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 143
3.3. Conservation status judged using only human
density and geographic range
In the new listing of conservation status tested here,
we use only two indices of risk, human density and
geographic range, the two indices with the most data.
While Threatened species experience higher human
densities than Lower Risk species, and on average have
smaller geographic ranges, meaning that geographic
range correlates with density (N=203; F=7.46;
P<0.01), the relationship between the two indices of
threat is not nearly tight enough for either to be used as
a surrogate of the other (r
We divide conservation status into three categories,
High, Intermediate, and Low Priority. High Priority taxa
experience high human density (more than the median)
in a small geographic range (less than the median);
Intermediate Priority taxa experience either high human
density in a large geographic range, or low human den-
sity in a small geographic range; and Low Priority taxa
experience low human density in a large geographic
range. We further divide the High and Low priority
categories. Thus Very High Priority species are those
with human density in their geographic range higher
than the upper quartile value for the globe, along with a
geographic range size lower than the lower quartile
value. Similarly Very Low Priority species would be
those with human density lower than the lower quartile,
and geographic range size above the upper quartile.
The new list (Table 1) is quite different from the cur-
rent one. Instead of just nine Critically Endangered pri-
mate species in the 1996 Red List, there are 54 High
Table 1 (continued)
Callithrix humeralifer 4 1.75 20.34 I
Callithrix hybrids 4* 46.22 19.40 H
Callithrix jacchus 4* 32.94 65.94 I
Callithrix kuhlii 4* 47.27 2.76 H
Callithrix nigriceps 3 1.01 1.41 I
Callithrix penicillata 4* 21.27 131.13 L
Cebuella pygmaea 4 1.27 135.94 L*
Cebus albifrons 4* 8.01 388.54 L*
Cebus apella 4* 14.05 1209.53 L
Cebus capucinus 4* 37.85 42.39 I
Cebus olivaceus 4* 7.92 198.47 L*
Chiropotes albinasus 4 2.52 66.58 L
Chiropotes satanas 4 4.66 205.74 L*
Lagothrix flavicauda 1* 8.52 0.57 I
Lagothrix lagotricha 4 4.64 352.46 L*
Leontopithecus caissara 1* 70.37 0.36 H
Leontopithecus chrysomelas 2* 22.73 3.57 I
Leontopithecus chrysopygus 1* 129.37 4.56 H*
Leontopithecus rosalia 1* 375.71 2.66 H*
Pithecia irrorata 4 1.77 137.95 L*
Pithecia monachus 4 2.35 111.76 L
Pithecia pithecia 4 2.62 178.15 L*
Saguinus bicolor 4* 18.57 5.78 I
Saguinus fuscicollis 4 3.16 169.66 L*
Saguinus geoffroyi 4* 28.21 6.06 I
Saguinus imperator 4 1.52 22.38 I
Saguinus inustus 4 0.46 36.06 I
Saguinus labiatus 4 0.93 29.49 I
Saguinus leucopus 3* 73.82 5.88 H
Saguinus midas 4 3.62 158.91 L*
Saguinus mystax 4 0.72 59.71 L
Saguinus nigricollis 4 4.66 26.84 I
Saguinus oedipus 2* 91.51 4.98 H*
Saguinus tripartitus 4 4.95 3.09 I
Saimiri sciureus 4 4.29 586.06 L*
IUCN status: 1=Critically Endangered; 2=Endangered; 3=Vulnerable; 4=Lower Risk. New CS: H=High Priority (above median human density/
below median geographic range); L=Low Priority (the opposite); I=Intermediate Priority. * in IUCN column indicate species with human densities
in their geographic range of more than the median for the continent, in other words species that might be especially at risk within each IUCN Red
List status. * in New CS column indicate species that are either Very High or Very Low Priority (above and below upper and lower quartiles for
density and range, accordingly).
144 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
Priority species (‘H’ in the Table’s New CS column).
Furthermore, 17 of these are currently listed in the Red
List as Low Risk (‘4’ in the IUCN column). The new
classification produces 15 Very High Priority species
(‘H*’), none of which is Low Risk. Instead of 128 Low
Risk species, there are 60 Low Priority species (L under
New CS), none of which is Critically Endangered in the
IUCN Red List, although two of them Endangered (‘2’
under IUCN). And 16 Very Low Priority species exist
(‘L*’), all of them previously Low Risk in the Red List.
All are in South America. Four Data Deficient species
become High Priority, and one is Low Priority.
4. Discussion
4.1. Threat as an additional Red List criterion
This study indicates that, in general, primate species
that are currently reacting poorly to threats (as judged
by current IUCN Red List status) are also especially
threatened, because they experience relatively high
human densities in their geographic range (Figs. 1 and
2). If the relationship between current status and human
density were tight, adding human density as another
criterion by which to judge status would not improve
Fig. 1. Human density within primate species’ geographic ranges by IUCN Red List conservation status of the species. Results are median species’
density at each status for each region. Low Risk=Lower Risk; Vuln=Vulnerable; End’d=Endangered; Crit. End=Critically Endangered.
Madag.=Madagascar; S/C Amer.=South and Central America. Details of statistical tests are given in Table 2.
Table 2
ANOVAR statistics for comparisons of human density across all four categories of conservation status (All), and between Threatened and Low Risk
categories (T vs LR); and for comparisons between Threatened and Low Risk categories when phylogeny is controlled for by comparative analysis
by independent contrasts (T vs LRCAIC), where the statistic is the zvalue from Wilcoxon matched pairs, signed rank tests of the results of the
comparative analysis by independent contrasts (N=50 contrasts)
Conservation Status Globe Africa Asia Madagascar S/C America
F/z P<F/z P<F/z P<F/z P<F/z P<
All (df=2–3) 9.15 0.0001 2.06 ns 3.08 0.04 1.50 ns 8.11 0.0001
T vs LR (df=1) 25.65 0.0001 2.81 0.1 7.10 0.02 0.15 ns 18.27 0.0001
TvsLRCAIC 3.63 0.001 1.52 ns 0.97 ns 0.0 ns 1.95 0.1
N=217 species (61 in Africa, 51 in Asia, 32 in Madagascar, and 73 in the Americas). Probability given as ‘ns’ when P>0.1.
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 145
the categorization of conservation status. However, the
relationship between current Red List status and human
density is very loose, so loose that within the three
Threatened Red List categories, no relationship at all
exists (Fig. 1).
Furthermore, the new classification of conservation
status tested here, which was based on geographic range
and human density alone (the two indices for which
most data are available), produced many differences
from the current Red List, which is based largely on
geographic range and population parameters (Table 1).
Unless one, or the other, or both lists are completely
invalid, the loose fit between human density and current
status, and the lack of match between two lists, each
based on sensible criteria, indicate that adding human
density as an explicit criterion might improve the use-
fulness of the current Red List, especially if the cate-
gorizations are altered to reflect the inevitable
uncertainty of the data (Akc¸ akaya et al., 2000).
At the very least, the addition of a separate criterion
of threat (measured as human density) would provide a
means to provisionally classify the current Data Defi-
cient species, so taking them out of the current vacuum
of effectively uncategorized status. More generally, the
addition, by providing an explicit measure of an
obvious component of risk, should make the assessment
of status more accurate. It should also make it more
usable, given that managers need to know why a species
is in danger before they can implement the best means
of preventing further or future decline.
While the more criteria used to assess a species’ con-
servation status, the more likely the classification is to
be accurate, there are drawbacks. More criteria means
more complexity and time in production of the list.
How might the addition of a criterion of threat most
simply and usefully be made?
The most seriously threatened species are the ones
that require the most immediate concern. These are
arguably the six species of the nine that IUCN (1996)
classified as Critically Endangered that we show to have
unusually high human densities within their geographic
range, namely Hylobates moloch (Asia), Pygathrix
avunculus (Asia), Hapalemur simus (Madagascar), and
Leontopithecus caissara,chrysopygus, and rosalia (South
America). The simplest change would simply be to
increase their status.
More generally, within each current category of Red
List status, the species facing the most threat are those
that occur in regions of higher than average human
density. The current listing could be simply refined
overall by raising the status of those species within
the current categories that experience greater than the
average human density. Callithrix kuhlii, Low Risk
according to the 1996 Red List (IUCN, 1996), dropped
from the 2000 List (IUCN, 2000), but a species with the
fifth smallest geographic range in the Americas and with
a human density in its range in the American upper
quartile (Table 1), is an example of a species whose Red
List status might need re-examination.
Human density is the measure of threat used here.
Human density is of course going to change, as will the
population size, geographic range and so on of the spe-
cies, and indeed their taxonomic status. Hence the con-
tinuous reassessment of conservation status that IUCN
conducts (IUCN, 2000). While the current threshold
criteria are absolute (e.g. more or less than a stated
threshold population size), our suggestion that species
at higher than median human density are given higher
status means the use of a relative measure. The measure
is relative in both time and space. We see no problem
with that, and indeed an advantage. The world will not
conserve all species; decisions of priority have to be
made; adding a criterion of above or below median
human density for the region (whether it be the globe or
the continent) is an explicit means of prioritization.
4.2. Problems with threat as a criterion
One problem with the use of high human density to
indicate potential risk is that Low Risk commensals,
such as the rhesus macaque, Macaca mulatta, and the
hanuman langur, Semnopithecus entellus, could achieve
high conservation status. In effect, ‘weed’ species would
be counted as threatened because of their association
with humans. However, a characteristic of most weed
species is that they have both large populations and
large geographic ranges. Thus, they should not be cate-
gorized as especially threatened. Such is the case with
the rhesus and hanuman langur.
Fig. 2. Summary comparison of log
human density within primate
species’ geographic ranges against the species’ IUCN Red List con-
servation status. ‘Threatened’ includes Vulnerable, Endangered, and
Critically Endangered species. Shown are medians, mean (square
symbol), interquartile range (box), and tenth percentile limits. Details
of statistical tests are given in Table 2.
146 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
However, one of Richard et al.’s (1989) ‘weed’ maca-
ques, Macaca sinica, appears in our High Priority list-
ing, based on human density and geographic range.
That is proper for two reasons. First, Richard et al.
debated on biological grounds whether to classify it as a
‘weed’ species. Second, and illustrative of the value of
adding threat as a criterion, the huge decline in rhesus
numbers between 1960 and 1980 (Richard et al., 1989)
demonstrates how quickly commensals can disappear.
Had human density been an explicit criterion of con-
servation status, perhaps the exploitation of this species
would have been stopped sooner, because its association
with high human density (nearly three times the median
Asian species’ average) would have flagged its Vulner-
able categorization.
A second problem with adding threat as a measure
could be agreement on the measure of threat. We have
used human density here, but the measure that best
correlates with extinction appears to vary with the
taxon considered. Thus Kerr and Currie (1995) showed
that the proportion of avian species at risk correlated
best with human density per country, but the propor-
tion of mammalian species correlated best with a
measure of economic performance of the country, gross
national product.
Nevertheless, we suggest that as a first order approx-
imation of potential risk—which is what the Red Data
Book categories are designed to indicate—human den-
sity is probably the most useful index of threat. Exten-
sive evidence indicates the damaging effects of high
human density (see Section 1), and extensive, precise,
and frequently updated data are available on human
4.3. Red Lists per taxon per continent?
The Red List scheme works by categorizing all animal
species, whether a beetle or a baboon, whether from
Botswana, Brazil, or Britain, according to whether they
cross certain common thresholds of rate of population
decline, or population size, and so on. However, not
only do species differ greatly in their inherent suscept-
ibility to extinction, but continents differ in their com-
plement of taxa, as well as in many aspects of
geography, including in their overall human density
within the geographic range of primates in each con-
tinent, and in the distribution of human densities across
the four categories of conservation status (Fig. 1).
In the present analysis, Asia and Madagascar stand
out as showing, respectively, consistently the highest
and lowest human densities across the geographic extent
of the four classes of conservation status of primates
(Fig. 1). In other words, primates in Asia survive as
Low Risk at far higher human densities than is the case
for the other three continents; and they move to more
threatened conservation status at far higher thresholds
of human density than is the case for the other three
continents. If Madagascar’s threshold human density
for Threatened status were applied to Asia, only three
Asian species would be Low Risk (5%), as opposed to
the present 20 (34%). Asian primates thus appear resis-
tant by comparison with primates from the other
regions, especially Madagascar.
If these differences are real, and especially if they
apply to other taxa than primates, we need to under-
stand why they exist, and possibly refine the Red List
categorizations accordingly. At present we can com-
ment briefly on the differences, but we have no good
general explanation for them.
Extant taxa in general have been argued to be more
resistant to extinction than in the past—because only
the resistant ones have survived the past changes (e.g.
Balmford, 1996). Thus the Pacific islands with the
longest human habitation have experienced the fewest
very recent extinctions, and similarly elsewhere (Mac-
Phee and Marx, 1997; McKinney, 1997). While tropical
Asia has a far higher human population density than
does any other tropical continent (the median density in
forested nations (those that could hold primates) is over
four times the other three continents’ median densities
(data from World Resources Institute, 2000), Asia
might not have had that high density for very long. For
instance, less than a millenium ago, southern China was
perhaps at least half forested, with sufficiently undis-
turbed forest that elephant and tigers were a nuisance
(Marks, 1998); and the Malay Peninsula and especially
Indonesia did not become densely populated until late
in the eighteenth century, since when about half of the
population has been on just Java (Brookfield et al.,
The arrival of humans in Madagascar about 2000
years ago was soon followed by vegetational changes,
and a peak of extinctions (MacPhee and Marx, 1997).
Resistant species should be left. However, it is also the
case that extremely little forest remains (Harcourt and
Thornback, 1990; Mittermeier et al., 1994; Goodman
and Patterson, 1997), and current ranges of extant spe-
cies are a fraction of their former ranges (Godfrey et al.,
1999). Perhaps, therefore, it is not intensity of threat
that separates the species, for all face the same intense
threat of loss of habitat, but rather only their differing
degree of susceptibility to threat?
Inability to explain these continental differences in the
relationship between human density and status means
that the decision to apply common criteria of conserva-
tion status to all animals might be too ambitious, or
hide too much. Knowing as we do that different taxa
react differently to the same threat, that continents dif-
fer in not only intensity but general nature of threats,
perhaps taxon-by-continent measures should be used,
especially in the absence of good explanations for the
continental differences highlighted here.
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 147
5. Conclusion
In conclusion, it is not just a species’ susceptibility to
threat, but also the threat itself that determines whether
a species is going to go extinct. Therefore, we suggest
that the Red List conservation status of taxa should
explicitly include measures of threat, as well as suscept-
ibility to threat. The easiest way of including threat
could be to use human density as an index, and to raise
the status of taxa found in regions of higher than med-
ian density for their continent. More generally, the
classification might be clearer and more usable if the
criteria were explicitly distinguished as, (1) threats
(human density and, perhaps, habitat loss); (2) species’
risk factors (size of population and of geographic
range); and (3) species’ response to threat (declining
population and geographic range)?
We thank Andy Purvis for providing an updated pri-
mates phylogeny coded for use by CAIC. For detailed
comments that considerably improved the paper, we
thank Monique Borgerhoff-Mulder, Tim Caro, Geor-
gina Mace, Kelly Stewart, and Truman Young (who
suggested the tripartite division of criteria listed in Sec-
tion 5).
Abacus Concepts, I., 1990–1991Statview SE+. Abacus Concepts,
Berkeley, CA.
Akc¸ akaya, H.R., Ferson, F., Burgman, M.A., Keith, D.A., Mace,
G.M., Todd, C.R., 2000. Making consistent IUCN classifications
under uncertainty. Conservation Biology 14, 1001–1013.
Balmford, A., 1996. Extinction filters and current resilience: the sig-
nificance of past selection pressures for conservation biology.
Trends in Ecology and Evolution 11, 193–196.
Balmford, A., Moore, J.L., Brooks, T., Burgess, N., Hansen, L.A.,
Williams, P., Rahbek, C., 2001. Conservation conflicts across
Africa. Science 291, 2616–2619.
Barnes, R.F.W., 1990. Deforestation trends in tropical Africa. African
Journal of Ecology 28, 161–173.
Bawa, K.S., Dayanandan, S., 1997. Socioeconomic factors and tropi-
cal deforestation. Nature 386, 562–563.
Brookfield, H., Lian, F.J., Kwai-Sim, L., Potter, L., 1990. Borneo and
the Malay Peninsula. In: Turner, B.L., Clark, W.C., Kates, R.W.,
Richards, J.F., Mathews, J.T., Meyer, W.B. (Eds.), The Earth as
Transformed by Human Action. Cambridge University Press,
Cambridge, pp. 495–512.
Brown, J.H., 1971. Mammals on mountaintops: nonequilibrium insu-
lar biogeography. The American Naturalist 105, 467–478.
Cincotta, R.P., Wisnewski, J., Engelman, R., 2000. Human population
in the biodiversity hotspots. Nature 404, 990–992.
Corbet, G.B., Hill, J.E., 1991. A World List of Mammalian Species.
Oxford University Press, Oxford.
Corbet, G.B., Hill, J.E., 1992. The Mammals of the Indomalayan
Region: A Systematic Review. Oxford University Press, Oxford.
Cowlishaw, G., Dunbar, R., 2000. Primate Conservation Biology.
Chicago University Press, Chicago.
Diamond, J.M., 1984. Historic extinctions: a Rosetta Stone for
understanding prehistoric extinctions. In: Martin, P.S., Klein, R.G.
(Eds.), Quaternary Extinctions. A Prehistoric Revolution. The Uni-
versity of Arizona Press, Tucson, Arizona, pp. 824–862.
Dobson, A.P., Rodriguez, J.P., Roberts, W.M., Wilcove, D.S., 1997.
Geographic distribution of endangered species in the United States.
Science 275, 550–553.
ESRI Inc., 1998a. ARC/INFO, 7.1.2.. Environmental Systems
Research Institute, Redlands, California.
ESRI Inc., 1998b. ArcView GIS, 3.1.. Environmental Systems
Research Institute, Redlands, California.
Ford, S.M., 1994. Taxonomy and distribution of the owl monkey. In:
Baer, J.F., Weller, R.E., Kakoma, I. (Eds.), Aotus: The Owl Mon-
key. Academic Press, San Diego, pp. 1–57.
Gaston, K.J., 1994. Rarity. Chapman & Hall, London.
Godfrey, L.R., Jungers, W.J., Simons, E.L., Chatrath, P.S., Rakoto-
samimanana, B., 1999. Past and present distributions of lemurs in
Madagascar. In: Rakotosamimanana, B., Rasamimanana, H.,
Ganzhorn, J.U., Goodman, S.M. (Eds.), New Directions in
Lemur Studies. Kluwer Academic/Plenum Publishers, New York,
pp. 19–53.
Goodman, S.M., Patterson, B.D., 1997. Natural Change and Human
Impact in Madagascar. Smithsonian Institution Press, Washington,
Groves, C.P., 1993. Order Primates. In: Wilson, D.E., Reeder, D.M.
(Eds.), Mammal Species of the World: A Taxonomic and Geo-
graphic Reference. Smithsonian Institution Press, Washington, DC,
pp. 243–277.
Hannah, L., Lohse, D., Hutchinson, C., Carr, J.L., Lankerani, A.,
1994. A preliminary inventory of human disturbance of world eco-
systems. Ambio 23, 246–250.
Harcourt, A.H., 1995. Population viability estimates: theory and
practice for a wild gorilla population. Conservation Biology 9, 134–
Harcourt, A.H., 1996. Is the gorilla a threatened species? How should
we judge? Biological Conservation 75, 165–176.
Harcourt, A.H., 1998. Ecological indicators of risk for primates, as
judged by susceptibility to logging. In: Caro, T.M. (Ed.), Behavioral
Ecology and Conservation Biology. Oxford University Press, New
York, pp. 56–79.
Harcourt, A.H., 2001. Primate evolution: a biology of Holocene
extinction and survival on the south-east Asian Sunda Shelf islands.
American Journal of Physical Anthropology 114, 4–17.
Harcourt, C.S., Thornback, J., 1990. Lemurs of Madagascar and the
Comoros. IUCN—The World Conservation Union, Gland.
Hershkovitz, P., 1987a. The taxonomy of South American sakis, genus
Pithecia (Cebidae, Platyrrhini): a preliminary report and critical
review with the description of a new species and a new subspecies.
American Journal of Primatology 12, 387–468.
Hershkovitz, P., 1987b. Uacaries, New World monkeys of the genus
Cacajao (Cebidae, Platyrrhini): a preliminary taxonomic review with
the description of a new subspecies. American Journal of Primatol-
ogy 12, 1–53.
Hershkovitz, P., 1990. Titis, New World Monkeys of the genus Calli-
cebus (Cebidae, Plattyrrhini): a preliminary taxonomic review.
Fieldiana Zoology 55, 1–109.
Hilton-Taylor, C., 2000. The IUCN/SSC Red List program: toward
the 2000 IUCN Red List of Threatened Species. Species 33, 21–29.
Hoare, R.E., Du Toit, J.T., 1999. Coexistence between people and
elephants in African savannas. Conservation Biology 13, 633–639.
IUCN, 1996. 1996 IUCN Red List of Threatened Animals. IUCN,
Gland, Switzerland.
IUCN, 2000. 2000 IUCN Red List of Threatened Species. Interna-
tional Union for Conservation of Nature and Natural Resources,
Gland, Switzerland. Available:
148 A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149
Jablonski, D., 1991. Extinctions: a paleontological perspective. Science
253, 754–757.
Jernvall, J., Wright, P.C., 1998. Diversity components of impending
primate extinctions. Proceedings of the National Academy of Sci-
ences USA 95, 11279–11283.
Kerr, J.T., Currie, D.J., 1995. Effects of human activity on global
extinction risk. Conservation Biology 9, 1528–1538.
Kinzey, W.G., 1997. New World Primates. Ecology, Evolution and
Behavior. Aldine de Gruiter, New York.
Laurance, W.F., 1991. Ecological correlates of extinction proneness in
Australian tropical rain forest mammals. Conservation Biology 5,
Leach, M.K., Givnish, T.J., 1996. Ecological determinants of species
loss in remnant prairies. Science 273, 1555–1558.
Lee, P.C., Thornback, J., Bennett, E.L., 1988. Threatened Primates of
Africa. The IUCN Red Data Book, IUCN, Gland.
Lernould, J.-M., 1988. Classification and geographical distribution of
guenons: a review. In: Gautier-Hion, A., Bourlie
`re, F., Gautier, J.P.,
Kingdon, J. (Eds.), A Primate Radiation: Evolutionary Biology of
the African Guenons. Cambridge University Press, Cambridge, pp.
Mace, G.M., 1995. Classification of threatened species and its role in
conservation planning. In: Lawton, J.H., May, R.M. (Eds.),
Extinction Rates. Oxford University Press, Oxford, pp. 197–213.
MacPhee, R.D.E., Marx, P.A., 1997. The 40,000-year plague: humans,
hyperdisease, and first-contact extinctions. In: Goodman, S.M., Pat-
terson, B.D. (Eds.), Natural Change and Human Impact in Mada-
gascar. Smithsonian Institution Press, Washington, DC, pp. 169–217.
Marks, R.B., 1998. Tigers, Rice, Silk, & Silt. Environment and Econ-
omy in Late Imperial South China. Cambridge University Press,
McKinney, M.L., 1997. Extinction vulnerability and selectivity: com-
bining ecological and paleontological views. Annual Review of
Ecology and Systematics 28, 495–516.
McKinney, M.L., 2001. Role of human population size in raising bird
and mammal threat among nations. Animal Conservation 4, 45–57.
McNeely, J.A., Gadgil, M., Leve
`que, C., Padoch, C., Redford, K.,
1995. Human influences on biodiversity. In: Heywood, V.H., Wat-
son, R.T. (Eds.), Global Biodiversity Assessment. Cambridge Uni-
versity Press, Cambridge, UK, pp. 711–821.
Mittermeier, R.A., Tattersall, I., Konstant, W.R., Meyers, D.M.,
Mast, R.B., Nash, S.D., 1994. Lemurs of Madagascar. Conserva-
tion International, Washington, DC.
Muchaal, P.K., Ngandjui, G., 1999. Impact of village hunting on
wildlife populations in the western Dja Reserve, Cameroon. Con-
servation Biology 13, 385–396.
Nash, L.T., Bearder, S.K., Olson, T.R., 1989. Synopsis of Galago spe-
cies characteristics. International Journal of Primatology 10, 57–80.
Niemitz, C., 1984. Taxonomy and distribution of the genus Tarsius
Storr, 1780. In: Niemitz, C. (Ed.), Biology of Tarsiers. Gustav
Fischer, Stuttgart, pp. 1–16.
Oates, J.F., Davies, A.G., Delson, E., 1994. The diversity of living
colobines. In: Davies, A.G., Oates, J.F. (Eds.), Colobine Monkeys.
Their Ecology, Behaviour and Evolution. Cambridge University
Press, Cambridge, pp. 45–73.
Parker, I.S.C., Graham, A.D., 1989. Men, elephants, and competition.
Symposia of the Zoological Society of London 61, 241–252.
Purvis, A., 1995. A composite estimate of primate phylogeny. Philo-
sophical Transactions of the Royal Society of London. B 348, 405–
Purvis, A., Rambaut, A., 1995. Comparative analysis by independent
contrasts (CAIC): an Apple Macintosh application for analysing
comparative data. Computer Applications in the Biosciences 11,
Purvis, A., Webster, A.J., 1999. Phylogenetically independent com-
parisons and primate phylogeny. In: Lee, P.C. (Ed.), Comparative
Primate Socioecology. Cambridge University Press, Cambridge, pp.
Richard, A.F., Goldstein, S.J., Dewar, R.E., 1989. Weed macaques:
the evolutionary implications of macaque feeding ecology. Interna-
tional Journal of Primatology 10, 569–594.
Robinson, J.G., Redford, K.H., Bennett, E.L., 1999. Wildlife harvest
in logged tropical forests. Science 284, 595–596.
Rylands, A.B., Coimbra-Filho, A.F., Mitermeier, R.A., 1993. Sys-
tematics, geographic distribution, and some notes on the conserva-
tion status of the Callitrichidae. In: Rylands, A.B. (Ed.), Marmosets
and Tamarins. Systematics, Behaviour, and Ecology. Oxford Uni-
versity Press, Oxford, pp. 11–77.
SAS Institute Inc., 1995. JMP, 3.2.2. SAS Institute, Cary, North
Terborgh, J., 1974. Preservation of natural diversity: the problem of
extinction prone species. Bioscience 24, 715–722.
Tobler, W., Deichmann, U., Gottsegen, J., Maloy, K., 1995. The
Global Demography Project. Center for International Earth Science
Information Network;
dem.doc.html (Technical report TR-95–6). National Center for
Geographic Information and Analysis. Department of Geography,
University of California, Santa Barbara.
Wolfheim, J.H., 1983. Primates of the World: Distribution,
Abundance and Conservation. University of Washington Press,
Woodroffe, R., 2000. Predators and people: using human densities to
interpret carnivore declines. Animal Conservation 3, 165–173.
World Resources Institute, 1998. World Resources, 1998–1999.
Oxford University Press, Oxford, New York.
World Resources Institute, 2000. World Resources, 2000–2001. World
Resources Institute, Washington, DC.
Wright, P.C., Jernvall, J., 1999. The future of primate communities: A
reflection of the present? In: Fleagle, J.G., Janson, C.H., Reed, K.E.
(Eds.), Primate Communities. Cambridge University Press, Cam-
bridge, UK, pp. 295–309.
A.H. Harcourt, S.A. Parks / Biological Conservation 109 (2003) 137–149 149
... We also tested the hypothesis that some traits previously shown to be associated with primate extinction risk are losing signal as more species become imperiled, for example, if anthropogenic threats are becoming so overwhelming that all species are beginning to suffer regardless of their attributes. This analysis involved repeating our analyses of threat status using an older IUCN threat status dataset and species list obtained from Harcourt & Parks [58]. ...
... When repeating our analyses of extinction risk with an older IUCN dataset documented in Harcourt & Parks [58], we found that insularity and home range size shared a positive relationship with binary and ordinal threat status, while other traits were not powerful predictors. This pattern of results using newer versus older data indicates that some traits (i.e. home range size) have become less powerful predictors of extinction in the past 20 or so years. ...
... Meanwhile, some traits identified in our analysis of ordinal 2021 threat status (i.e. group size and omnivory) do not emerge in analyses with older data indicating these traits may be beginning to have a larger signal over time. However, it is also possible that the larger number of species in our 2021 dataset (a consequence of taxonomic reevaluations in many clades [31]) and general improvements in the thoroughness and accuracy of IUCN assessments since Harcourt & Parks [58] provided the statistical power to detect the effects of these traits. ...
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Explaining why some species are disproportionately impacted by the extinction crisis is of critical importance for conservation biology as a science and for proactively protecting species that are likely to become threatened in the future. Using the most current data on threat status, population trends, and threat types for 446 primate species, we advance previous research on the determinants of extinction risk by including a wider array of phenotypic traits as predictors, filling gaps in these trait data using multiple imputation, and investigating the mechanisms that connect organismal traits to extinction risk. Our Bayesian phylogenetically controlled analyses reveal that insular species exhibit higher threat status, while those that are more omnivorous and live in larger groups have lower threat status. The same traits are not linked to risk when repeating our analyses with older IUCN data, which may suggest that the traits influencing species risk are changing as anthropogenic effects continue to transform natural landscapes. We also show that non-insular, larger-bodied, and arboreal species are more susceptible to key threats responsible for primate population declines. Collectively, these results provide new insights to the determinants of primate extinction and identify the mechanisms (i.e. threats) that link traits to extinction risk.
... It is also known that these species are favorites in zoos (Fragaszy et al., 2004) and are prone to initiate friendly interactions with nature-park visitors and ecotourists (McKinney, 2014;Valença et al., 2021). However, conflicts, such as deforestation and habitat loss, tend to arise as interactions become more frequent (Estrada et al., 2018;Ferreira et al., 2009;Fuentes, 2012;Harcourt & Parks, 2002;Rajão et al., 2020). Through Google, we found reports of capuchins attacking people, raiding crops, invading houses and apartments, facing environmental disasters (e.g., fires, oil spills), facing threats of yellow fever, being run over by cars, and shocked by electrified wires. ...
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There remains a debate as to whether the display of wild animals inpopular media, such as the Internet, contributes toward or erodesconservation behavior. A good model to assess these impacts arecapuchin monkeys (genera Cebus and Sapajus), given that theyhave historically been traded as pets internationally and areamong Hollywood’s most famous primate actors. We usedcrowdsourcing tools to survey social media posts (YouTube andInstagram) and news/reports (on Google) to investigate howthese primates are currently portrayed on the Internet. We found1138 capuchin-related videos on YouTube, and the ones withmore than 1 million views mainly (71%) portrayed these animalsas pets. Searches on Instagram identified that #capuchinmonkeyhad 39,000 more posts than #Cebus or #Sapajus, of which the topresults (those that generated the most engagement) were postsof individuals in anthropogenic environments and/or close tohumans. Our Google search identified an exponential growth ofnews related to the legal and illegal pet trade of capuchinmonkeys since 2017, which could be related to the increase onthe reach and engagement of social media posts with theseprimates as pets. Poor scientific knowledge or interest, along withengagement with exotic pet trade content among Internet users,may lead to negative consequences for species conservation.Given the threats facing both capuchin monkeys and otheranimals, including increasing habitat fragmentation and loss, it isessential to establish clear policies surrounding wildlife contentmanagement on social media.
... All identified species were also compared with the Red List of threatened species of the Czech Republic (Hejda et al., 2017). For every orchard, the threatened species index (Harcourt and Parks, 2003) was calculated. This index consisted of a threat category number (near threatened (1), vulnerable (2), endangered (3) and critically endangered (4)) multiplied by the number of individuals from every category in the orchard. ...
Fruit orchards under different types of management represent the most common agroforestry practice in central Europe. Traditional fruit orchards with trees usually planted in meadows are at a surplus, providing suitable habitats for many plant and animal species. We examined the influence of different management and biotope types on three insect groups. This study was conducted in thirty orchards across the capital city of the Czech Republic – Prague (496 km²). We investigated the diversities of butterflies, hymenopterans and beetles. Their species richnesses mainly benefitted from orchard management and was partly higher at the xerothermic sites than at the mesic sites. Red-listed species did not show any clear patterns. Open-landscape specialists were influenced by management, while forest species were influenced by habitat type. Generally, orchard abandonment led to insect biodiversity loss. Therefore, active agricultural management appears to be essential for insect biodiversity conservation in orchards, and different management and biotope types provide suitable conditions for specific species. Mowing and maintaining orchards are two important biodiversity management actions in terms of maintaining large-scale and long-term species diversity.
... It is a well-known fact that primate species are very selective in their diet, omnivorous in nature, 60 % of the diet is fruits, fruits, and flowers of Cullenia exarillata and mainly Ficus spp fruits (Kumar, 1987;Sushma et al., 2014). Further, composition of fruits and flowers are varying in every degree coordinate of the location, and macaques are forced to select their required food items to meet its nutrient requirements due to variation in rainfall pattern, temperature variation, and forest fire restrict the foraging activities of LTM, leads a greater risk of extinction (Harcourt and Parks, 2003).They predominantly eating fruits and flowers from December to February and May to July (Kurup and Kumar, 1993) and other months moving across the forest to look for fruiting trees. When their favoured food trees are not in fruiting and macaques depend on the flowers of Cul-lenia and a seasonal and non-synchronous fruits of Ficus. ...
... According to previous researches, habitat loss or degradation, over-harvesting, and intrinsic factors of the species are the three most serious threats for angiosperms in China (Qin and Zhao, 2017;Qin et al., 2017b). Due to these kinds of pressure, especially the anthropogenic impacts, many species and populations have declined or gone extinct (Davies et al., 2006;Di Marco and Santini, 2015;Di Marco et al., 2018;Feng et al., 2017;Harcourt and Parks, 2003). However, quantitative studies on the relationships between anthropogenic impacts and the selectivity of extinction risk are still rare, especially on plants in China (Feng et al., 2017). ...
Concentrating limited resources to protect as many species as possible is the most effective way to improve conservation efficiency, of which identifying the clustering characteristics of species in urgent need of conservation is a prerequisite. In this study, selectivity was used to characterize the taxonomic and geographic clustering characteristics of extinction risk for threatened spermatophytes in China. Results showed that the number of threatened species was highly clustered in taxonomy, floristic regions, and at the county scale. Clustering of threatened species was detected in 18 orders, 53 families, and 201 genera, account for 15.0 %–32.8 % of the total and 52.5 %–71.3 % of the threatened spermatophyte species. 18 out of 57 floristic regions and subregions were over-threatened. 298 counties (10.1 % of China's territory) were over-threatened, covering 83.4 %, 79.3 % and 80.3 % of the total species, threatened species and endemic species, respectively. Counties with the top 10.0 % species richness (SR), threatened species richness (TR) and endemic species richness (ER) covered 79.5 %, 70.3 % and 75.0 % of the total species, threatened species and endemic species, respectively, while covering only 5.7 % of the area of China. More than half of the counties with the top 10.0 % SR, TR and ER, as well as those over-threatened, were outside the existing conservation strategy and action plan. Areas most at risk were also found to be moderately affected by human influence (evaluated by human influence index (HII)) in China. This study provides a new perspective for the study of conservation priority in taxonomic groups and geographical areas.
... Several ways of mitigating this have been suggested including the use of SDM to provide a more quantitative assessment of the threats ) and adding human density as a category in the geographical range criteria (Harcourt and Parks 2003). One potential way of more robustly categorising the threats facing a species would be to combine regional assessments (if such assessments are available), taking into account the current threats as well as the political and economic situations and legal frameworks surrounding conservation in the country. ...
Habitat loss is the number one threat to terrestrial mammalian species. Paraguay is heavily reliant on industrial agriculture. Its Upper Paraná Atlantic Forest (BAAPA) had one of the world’s highest deforestation rates. This study examined the ecology of hooded capuchins at two sites; comparing dietary and sleeping site preferences and estimated habitat use, developing species distribution models, underpinned by LANDSAT 8 data. Results show the capuchin is an adaptable, forest obligate, requiring some level of forest cover. Capuchins don’t use degraded forest homogenously, preferring older growth areas, larger trees with more canopy connections for sleeping in degraded areas, and areas with higher soil and canopy moisture – a measure of forest maturity. They used the forest more uniformly at the more pristine site, frequently exploiting pine plantations for food and sleeping. The probability of capuchins occupying any area decreased to <50% when <33% of the forest remained. Between 2000-2019, across its full range, 25% of highly suitable forest was lost. Number of suitability fragments increased, as did the distance between highly suitable fragments. The Extent of Occurrence (EOO), estimated from suitable habitat availability (IUCN Red List Criterion B), matches expectation for ‘Near Threatened’. In Paraguay 58.4% of highly suitable forest was lost over 2000-2019 leaving an EOO of 9,368km2. Capuchins should be considered ‘Vulnerable’ in Paraguay given the high fragmentation of habitat, large distance between fragments, small amount of suitable forest remaining, and extreme, rapid habitat loss. The capuchin is suitable as a flagship and umbrella species for BAAPA conservation and restoration. Use of the pine plantation highlights opportunity for reforestation programs that can benefit local economies, creating corridors between forest fragments using native trees, mixed with shade-grown yerba mate bordered by pine plantations. Landowners would profit from the pine timber/yerba mate and wildlife would benefit from increased forest connectivity.
... Most sightings of this species took place in the two forest fragments closest to the main village of Kianjavato (Tsitola and Sangasanga), which could explain this finding. Other studies have found that proximity to human settlements and the associated anthropogenic disturbance negatively impacts primate species, including ruffed lemurs (Harcourt & Parks, 2003;White et al., 1995). It seems likely that V. variegata is instead selecting habitat based on correlated, unmeasured covariates | 7 of 12 (e.g., resource availability). ...
Primate species face growing risks of extinction throughout the world. To better protect their populations, effective monitoring techniques are needed. The goal of this study was to evaluate the use of arboreal camera traps and occupancy modeling as conservation tools for threatened lemur species. This project aimed to (1) estimate the occupancy and detection probabilities of lemur species, (2) investigate factors potentially affecting lemur habitat use, and (3) determine whether ground or arboreal cameras are better for surveying lemur assemblages. We conducted camera trapping research in five forest fragments (total trap nights = 1770; 900 arboreal trap nights (134 photo events); 870 ground trap nights (2 photo events)) and reforestation areas (total trap nights = 608; 1 photo event) in Kianjavato, Madagascar from May to September 2019. We used arboreal trap data from fragments to estimate occupancy for five species: the red-fronted brown lemur (Eulemur rufifrons; ψ = 0.54 ± SD 0.03), Jolly's mouse lemur (Microcebus jollyae; ψ = 0.14 ± 0.17), the greater dwarf lemur (Cheirogaleus major; ψ = 0.42 ± 0.30), the red-bellied lemur (Eulemur rubriventer; ψ = 0.24 ± 0.03), and the black-and-white ruffed lemur (Varecia variegata; ψ = 0.24 ± 0.08). Tree diameter, elevation, distance to village, and canopy connectivity were important predictors of occupancy, while camera height, canopy connectivity, fragment ID, and fragment size predicted detection. Arboreal cameras recorded significantly higher species richness compared with ground cameras. We suggest expanded application of arboreal camera traps in future research, but we recommend longer trapping periods to better sample rarer species. Overall, arboreal camera trapping combined with occupancy modeling can be a highly efficient and useful approach for monitoring and predicting the occurrence of elusive lemur species and has the potential to be effective for other arboreal primates and canopy taxa across the globe.
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(Chinese Title: 中国东部灵长类及其他常见兽类的分布变迁:1573~1949——基于地方志与 GIS 技术的量化分析. The final version was submitted to Sun Yat-sen University Library and The Ministry of Education of the People's Republic of China on December 22, 2022.) Background: Primatology is an important branch of biological anthropology, and it is a cross-disciplinary area with biology, psychology, etc.. Humans are causing the 6th Mass Extinction since several hundred years ago. The long-term co-existence between people and wild animals exerted a long-term and formative influence on the distribution of animals. And mammals, especially primates and other large/medium-sized mammals, had a particularly close relationship with people and were affected severely, thus become important indicators of ecological change. The human population of China, especially in eastern China, increased rapidly from the late Ming Dynasty to the Republic of China (ROC), and the distribution of wild animals including primates was greatly affected. Numerous local gazetteers in Ming dynasty, Qing Dynasty and ROC are well preserved today, and their records of local products are valuable resources for researching the historical biodiversity. However, previous studies only focused on the records of present animal and ignored the records of absent animal, resulting in obvious biases, and there is still a lack of quantitative studies. In order to understand the changes of the distribution of mammals and the influence from the population increasing in China better, I made full use of the records in local gazetteers to reconstruct the distribution of mammals and analyzed the distribution history of large and medium-sized mammals quantitatively. Methods: I established the Database of Wild Mammal Records in Chinese Local Gazetteers. And innovatively, I fixed the biases in previous researches, i.e. I analyzed the historical changes of biodiversity by using the data of both presence and absence records of mammals. In eastern China from 1573 to 1949 (sorted into 4 periods), I reconstructed the distribution of 14 kinds of mammals which sorted in 5 functional groups with ecological values by using ArcGIS 10.3 software. The mammals are: (1) primates: “yuan” - gibbons & Colobinae(including langur monkeys and snub-nosed monkeys, different to modern taxonomy in Chinese) and “hou” - macaque monkeys; (2)large carnivores: tigers, leopards and bears; (3)medium-sized carnivores: wolves, foxes, “li”(civets, including Felinae and Viverridae, different to modern taxonomy in Chinese), dholes and mustelids; (4)large deer: large deer as a whole (including moose); (5)medium-sized deer: “Zhang-She”(including water deer and musk deer), muntjac deer and roe deer. I used statistical software, e.g. SPSS, Fragstats and SmartPLS, to analyze the changes of distribution(area, altitude, slope gradient and fragmentation index) and the impact from the increase of human population. And analyzed the indexes of functional group richness and species(kinds) richness combined with the relevant events of human population history, to show ecological environmental changes in each provincial-level administrative regions. Results: (1)In general in all periods, with the increase of human population, the distribution area of primates, large carnivores, large-sized deer and medium-sized deer retracted, the mean altitude and mean slope gradient increase and the distribution changed from distributed widely to be confined in mountainous areas with high altitudes and high slopes, as the “refuge effect”. (2)The distribution of medium-sized carnivores expanded in general, confirming to be a typical ecological decline phenomenon - mesopredator release. The mean altitude and mean slope gradient also increase, but meaning expand from plains to mountains. (3)The ecological environment in the research area deteriorated with the increase of human population, but some areas in some periods recovered temporarily after specific events e.g. wars in Sichuan in late Ming–early Qing, Taipingtianguo rebellion, muslin anti-Qing revolts in Tongzhi reign. Conclusion: (1)Based on the reconstruction, I provide directive evidences of the human interference on the historical distribution of mammals, and show the specifics. Thus, quantitatively, I prove that the increase of local human population played a significant role in this process. The stereotype “wild large/medium-sized mammal live in hilly areas” is not a natural status but a man-made phenomenon in long term. The results provide a support for further researches. (2)Pioneeringly, I discovered that the environment in eastern China experienced the mesopredator release phenomenon in recent centuries, providing a base for further researches by researchers. (3)And my innovative reorganization of local gazetteers and the application of quantitative methods also provide examples for similar further researches. Keywords: Primate; Local Gazetteer; Historical Zoogeography; Quantitative History; 6th Mass Extinction 背景:灵长类学是生物人类学的重要分支,也是人类学与生物学、心理学及其他学科的交叉领域。数百年来,人类正逐步造成第六次物种大灭绝。人类与野生动物长期相处,对动物分布格局产生了长期且塑造性的影响,而兽类(即哺乳纲动物)尤其是包括灵长类动物在内的大中型兽类与人类关系密切,受影响亦尤为明显,是生态变化的重要指示性物种。明后期至民国是中国,尤其是中国东部人口急速增长的时期,灵长类等大中型兽类分布受影响明显,且该时期地方志资源丰富,明代、清代及民国时期的地方志大量保存至今,其对各地物产的记载是研究历史上生态多样性的宝贵资源。但已有相关研究只关注动物在当地分布(Presence)的记录,而忽略了动物在当地不分布(Absence)的记录,造成明显偏差,且量化研究尚十分欠缺。为更清楚地了解灵长类等兽类分布变化及其受到中国人口剧增的影响,笔者充分利用地方志中的记载,重拟各类曾广泛分布的灵长类等大中型兽类分布情况并量化分析其分布变迁历史。 方法:笔者建立了中国地方志兽类记录数据库,创新性地修正已有研究的偏差,在新方法中同时使用兽类分布与不分布的数据插值制图重拟其分布的历史变迁。以1573年(万历元年)至1949年间(分四阶段)的中国东部大陆地区为时空范围,笔者使用地理信息系统软件ArcGIS 10.3重拟14类兽类动物的分布,并根据生态意义将这些兽类划分为5个生态功能群,即(1)灵长类功能群:猿类(长臂猿以及含叶猴与金丝猴在内的疣猴,与现代科学分类体系所指猿类不同)、猴类(猕猴属);(2)大型食肉兽类功能群:虎、豹类、熊类;(3)中型食肉目兽类功能群:狼、狐类、狸类(猫亚科与灵猫科,与现代科学分类体系所指狸类不同)、豺、鼬类;(4)大型鹿类功能群:大型鹿类整体(含麋);(5)中型鹿类功能群:獐麝类(獐与麝类)、麂类、狍。笔者通过SPSS、Fragstats、SmartPLS等统计软件量化分析分布的面积、海拔、坡度与破碎化程度等变化情况及分析人口剧增对动物分布的影响;并根据功能群数与大中型兽类种类数两种指标对各省区的大中型兽类多样性变化进行梳理,结合人口史资料研究当地生态变迁。 结果:(1)总体上,随着人口剧增,灵长类、大型食肉目兽类、大型鹿类及中型鹿类的分布面积均有不同程度的缩减,分布平均海拔与平均坡度均有所提升,其分布从较广泛分布缩减至主要在高海拔大坡度的山地分布,产生“避难所效应”。(2)而中型食肉目兽类的分布总体上实现了扩张,经证实为中型捕食者释放效应这一典型的生态衰退现象,其分布平均海拔与平均坡度亦有所提升,但主要为从平原地区向山地扩散。(3)量化证实研究区域的大中型兽类多样性总体上随着人口增长而恶化,但明末清初四川战乱、太平天国运动、同治年间回民反清斗争等事件后部分地区的多样性在特定阶段有所恢复。 结论:(1)基于重拟,笔者给出了历史上人类干扰灵长类等大中型兽类分布的直接证据并展示了具体变化过程,量化证实中国东部人口增长在大中型兽类分布缩减过程中起了明显的作用,“大中型兽类主要在山地分布”这一刻板印象并非自然状态,而是人类长期塑造的结果,为学界提供了进一步研究的支持。(2)笔者首次发现了近世中国东部经历了中型捕食者释放效应现象,为学界提供了进一步研究的基础。(3)同时笔者对地方志动物记载的创新性整理及量化处理,也将为将来类似研究提供范例。 关键词:灵长类,地方志,历史动物地理学,量化历史学,第六次大灭绝
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Fruit orchards under different types of management represent the most common agroforestry practice in central Europe. Traditional fruit orchards with trees usually planted in meadows are at a surplus, providing suitable habitats for many plant and animal species. We examined the influence of different management and biotope types on three insect groups. This study was conducted in thirty orchards across the capital city of the Czech Republic – Prague (496 km²). We investigated the diversities of butterflies, hymenopterans and beetles. Their species richnesses mainly benefitted from orchard management and were partly higher at xerothermic sites than at mesic sites. Red-listed species did not show any clear patterns. Open-landscape specialists were influenced by management, while forest species were influenced by habitat type. Generally, orchard abandonment led to insect biodiversity loss. Therefore, active agricultural management appears to be essential for insect biodiversity conservation in orchards, and different management and biotope types provide suitable conditions for specific species. Mowing and maintaining orchards are two important biodiversity management actions in highly human-populated landscapes.
In just the last few years, behavioral ecologists have begun to address issues in conservation biology. This volume is the first attempt to link these disciplines formally. Here leading researchers explore current topics in conservation biology and discuss how behavioral ecology can contribute to a greater understanding of conservation problems and conservation intervention programs. In each chapter, the authors identify a conservation issue, review the ways it has been addressed, review behavioral ecological data related to it, including their own, evaluate the strengths and weaknesses of the behavioral ecological approach, and put forward specific conservation recommendations. The chapters juxtapose different studies on a wide variety of taxonomic groups. A number of common themes emerge, including the ways in which animal mating systems affect population persistence, the roles of dispersal and inbreeding avoidance for topics such as reserve design and effective population size, the key role of humans in conservation issues, and the importance of baseline data for conservation monitoring and modeling attempts. Each chapter sheds new light on conservation problems, generates innovative avenues of interdisciplinary research, and shows how conservation-minded behavioral ecologists can apply their expertise to some of the most important questions we face today.
Starting with concise species accounts for all the marmoset and tamarin monkeys, this important new book then goes on to review their geographical distributions and still-contested taxonomy, along with comparative reviews of vocalizations, scent-marking, mating systems, infant care and development, social organization, and behaviour and ecology in the wild. As several of these small primates are rare or threatened, these subjects are strongly relevant to their management in captivity as well as for understanding natural populations. This is the first volume for several years to review current knowledge of this family, which comprises 52 species and subspecies found from Panama to northeastern Paraguay to southern Brazil.
Although the behaviour and ecology of primates have been more thoroughly studied than that of any other group of mammals, there have been very few attempts to compare the communities of living primates found in different parts of the world. In Primate Communities, an international group of experts compares the composition, behaviour and ecology of primate communities in Africa, Asia, Madagascar and South America. They examine the factors underlying the similarities and differences between these communities, including their phylogenetic history, climate, rainfall, soil type, forest composition, competition with other vertebrates and human activities. As it brings together information about primate communities from around the world for the very first time, it will quickly become an important source book for researchers in anthropology, ecology and conservation, and a readable and informative text for undergraduate and graduate students studying primate ecology, primate conservation or primate behaviour.
There are some common dynamic forces of transformation, and it is a major object of this chapter to elucidate these forces and to show how they determine the manner in which resources are exploited and the earth is transformed. One major force is population growth, currently at a natural rate of about 2.5%/annum in both regions, but substantially supplemented by immigration. At the time of the 1980 censuses, the Peninsula had 11.4 million people and Borneo 9.3 million in a much larger area. By the mid-1980s, the Peninsula had some 13 million and Borneo almost 11 million. Because of the large illegal element in movement, official estimates for the mid-1980s understate the actual numbers. The peoples of Southeast Asia have developed systems of sustaining an ecological balance - ladang (swiddens) under one set of conditions of ecology and population; sawah (wet-rice fields) and kampung (villages and their gardens) under another. Around both lies the resource frontier of the forests. The equatorial lands we have surveyed were for centuries a source of profit for their rulers, then on a larger scale for the colonial capitalist system, and last, on a larger scale yet for the powerful, successful, and enterprising in the independent nations of Indonesia and Malaysia. With the possible exception of Javanese transmigrants and the poor and unemployed who have become timber cutters, those who have recently transformed the environment in damaging ways have done so for profit or in the name of development, and not from necessity. -from Authors
Holocene cave, marsh, and stream deposits on the island of Madagascar have yielded thousands of “subfossil” specimens that document recent megafaunal extinctions. Excavations conducted during the past 15 years of archaeological and paleontological sites in northern, northwestern and southwestern Madagascar have unearthed, in addition to new specimens of extinct lemurs and other megafauna, an abundance of bones of still-extant lemur species. These specimens, as well as specimens of extant lemurs from subfossil sites excavated in the early and mid-1900’s, prove that living lemur species once had much broader geographic ranges than they have today, and they help to explain the currently disjunct distributions of a number of species. This paper examines the pattern of distribution of extant primate species at subfossil sites, and compares recent to modern primate communities.