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Original Article

Using Ecological Niche Modelling to Predict Spatial and Temporal Distribution Patterns in Chinese Gibbons: Lessons from the Present and the Past

Chatterjee H.J.a · Tse J.S.Y.a · Turvey S.T.b

Author affiliations

aResearch Department of Genetics, Evolution and Environment, University College London, and bInstitute of Zoology, Zoological Society of London, London, UK

Corresponding Author

H.J. Chatterjee, Research Department of Genetics,

Evolution and Environment

University College London, Gower Street

London WC1E 6BT (UK)

E-Mail h.chatterjee@ucl.ac.uk

Related Articles for ""

Folia Primatol 2012;83:85–99

Abstract

Ecological niche modelling (ENM) is used to predict species’ tolerance to changing environmental conditions. Understanding changes in the spatial distribution of species across time is essential in order to develop effective conservation strategies. Here we map the past and present distribution of gibbons across China, a country experiencing extensive anthropogenic habitat destruction and ongoing biodiversity loss. The distribution of gibbons across three time intervals is described based on fossil, historical and modern-day data, and ENM, implemented using DIVA-GIS, is used to predict how modern-day gibbon distributions might respond to future climate change. Predictions based on modern-day data alone fail to reveal patterns of environmental tolerance and geographical distribution shown by gibbons in the relatively recent historical period, emphasizing the need to incorporate past as well as present data in conservation analyses.

© 2012 S. Karger AG, Basel


Keywords

China · Gibbons · Climate change · Range shifts · Geographic information system · DIVA-GIS · Ecological niche modelling ·


Introduction

Ecological niche modelling (ENM) is an increasingly popular method for mapping species’ distributions across space and time [Waltari and Guralnick, 2009]. Quantifying changes in the spatial distribution of species across time can provide valuable information regarding biogeography, palaeo-ecology and macro-evolution [Stigall and Lieberman, 2006]. Modelling these changes, using approaches such as ENM, affords an opportunity to predict species’ tolerance to changing environmental conditions [Hijmans and Graham, 2006], which in turn can be used to generate conservation action plans for threatened species, including primates [Thorn et al., 2009].

Recent historical changes to species’ geographical distributions are intrinsically linked to anthropogenic processes, with human-caused habitat loss and fragmentation responsible for driving range change in numerous taxa [Cowlishaw and Dunbar, 2000; Mace et al., 2008]. There is now evidence that human-induced climatic change is also increasingly affecting species’ geographical distributions [Parmesan, 1996, 2006; Moore, 2003]. It is therefore necessary to investigate spatial and temporal patterns of range change in different species in order to develop a better understanding of the ‘dynamic biogeography’ of range contraction, and to identify appropriate conservation management responses [Lomolino and Channell, 1995; Channell and Lomolino, 2000a, b; Turvey et al., 2010]. This is particularly important for geographical regions such as eastern and south-east Asia, which are currently experiencing extensive habitat destruction and which contain extremely high levels of threatened species [Schipper et al., 2008].

China has experienced high human population densities and associated anthropogenic environmental impacts for thousands of years [Zhang and Lin, 1992; Duan et al., 1998]. It is also one of the fastest developing countries in the world, with significant recent economic and industrial development and extensive deforestation due to increasing demand for land [Zhang and Lin, 1992; Wang, 2000]. Since the establishment of the People’s Republic of China in 1949, the country’s population has grown dramatically, reaching 1.34 billion in 2011 [CIA World Factbook, 2011]. Anthropogenic pressures on the environment in China resulting from industrialization combined with escalating human population density have driven population declines, extirpations and extinctions in many species, and extinction events continue to be documented from the region [Li et al., 2002; Rookmaaker, 2006; Yang et al., 2008; Wen, 2009; Turvey et al., 2010]. China’s climate is also now becoming warmer and more temperate due to global warming [Shen and Varis, 2001; Liu et al., 2010], which is likely to result in significant changes to ecosystems and species ranges in the near future.

Gibbons (family Hylobatidae) comprise between 14 and 18 species [Chatterjee, 2009; Israfi et al., 2011], of which 6 extant species are known to have occurred in China during the recent historical period [Geissmann, 2007; IUCN, 2011; Thinh et al., 2010]: Hoolock leuconedys (western hoolock), Hylobates lar (white-handed gibbon), Nomascus concolor (black-crested gibbon), N. hainanus (Hainan gibbon), N. leucogenys (white-cheeked gibbon) and N. nasutus (Cao Vit gibbon). All of these species are listed as endangered or critically endangered by the IUCN [2011], and the Hainan gibbon (N. hainanus) is now recognized as the world’s rarest and most threatened primate, with an estimated surviving global population of <25 individuals [Chan et al., 2005; Fellowes et al., 2008]. Gibbons are extremely dependent upon forested environments, spending nearly all of their time in the canopy [Chatterjee, 2006]. Human-caused deforestation has resulted in widespread population declines and ongoing range contraction and fragmentation in all Chinese gibbon species during recent decades [Zhang et al., 2010; IUCN, 2011], with H. lar and N. leucogenys possibly now extirpated from China [Fan and Jiang, 2009; Grueter et al., 2009; IUCN, 2011]. Gibbon populations in China have also experienced anthropogenic pressures during older historical periods, and large-scale environmental changes throughout the Quaternary [van Gulik, 1967; Jablonski and Chaplin, 2009; Wen, 2009]. However, no quantitative studies have yet been carried out to investigate spatiotemporal patterns of range shifts in Chinese gibbons, or how the current remnant distribution of gibbons is likely to be affected in the future by ongoing environmental change in China. Our study addresses these two key issues and provides new insights into the biogeographical pattern of gibbon range shifts available from both present-day and past distributional point locality data for Chinese gibbons.

Methods

We compiled a database comprising independent point locality data for each known gibbon record (fossil material, historical account or modern sighting record), including taxonomic information (species name if known), locality, province, time period, and latitude and longitude for each data point. The database comprises a total of 724 locality points (74 fossil, 607 historical, 43 modern records). Locality data for Chinese gibbons were compiled from the published literature across three time intervals: fossil (Pliocene to earliest Holocene), historical (AD 265–1945) and modern (AD 1945 to the present).

Data from the Holocene, including both the historical era and youngest fossil record, almost certainly represent environmental conditions that are closely similar to those found today [Roberts, 1998], whereas older fossil records instead represent different environmental conditions. However, although some of our Late Quaternary fossil records may represent Holocene samples, these are poorly dated and may alternately represent records from the Late Pleistocene or before. Although historical records, including ancient Chinese records [Jenyns, 1954; Wei, 1988], can often be difficult to interpret or identify accurately to species level [Turvey, 2009], gibbons were culturally significant animals in ancient China that are relatively easily identifiable in old texts, and about which a fairly considerable literature now exists [van Gulik, 1967; Geissmann, 2008; Wen, 2009]. Point locality data for modern distributions are surprisingly scarce despite several sources, such as the IUCN [2011], providing distribution range maps. Here we rely on 3 key references [Yi, 1986; Jablonski and Chaplin, 2009; Wen, 2009] that document gibbon distributions over time with associated point locality records, but recognize that these data do not represent all known localities. Any spurious data points which fell outside the ranges shown in the IUCN [2011] distribution maps were excluded from analysis. GPS points (comprising latitude and longitude coordinates) for gibbon localities were obtained either from Jablonski and Chaplin [2009] or from an internet-based GPS coordinates search tool (available at http://www.maps.google.cn). Gibbon distribution maps were produced using geographic information system (GIS) software (DIVA-GIS version 7.1.7, available at http://www.diva-gis.org). DIVA-GIS is a programme which uses GIS for mapping and analysing spatial data [Hijmans et al., 2005]. A number of analytical functions within DIVA-GIS permit ENM using the BIOCLIM and DOMAIN algorithms [Hijmans et al., 2005]. These functions were deployed to make predictions regarding gibbon range changes in response to climatic changes.

Modelling the Spatiotemporal Distribution of Gibbons in China

A location map of China available from DIVA-GIS (online supplementary figure 1, see www.karger.com?doi=10.1159/000342696) was used as the basis for modelling gibbon distributions. Data points from the locality database were imported into DIVA-GIS to produce a series of maps showing different distributional ranges for gibbons in China in each of the three studied time intervals. Each locality point from the database, which is defined by a specific observational record or fossil, is allocated an individual point on the resulting maps, to provide a composite picture of species level or multi-species ranges. For the purposes of analysis and to facilitate direct comparison between data from different time intervals, all gibbon species were interpreted as having the same niche and habitat requirements to provide a single index of gibbon habitat suitability, although we recognize that this is a necessary simplification.

ENM Using BIOCLIM

ENM was used to generate a series of models of present-day annual mean temperature and precipitation patterns in China, and to predict suitable habitats for gibbons in China given these present-day climatic conditions. In addition, mean temperature and precipitation variables were manipulated in line with future climate change predictions to model the effects of changing these variables on habitat suitability. DIVA-GIS provides a comprehensive global climate data set (BIOCLIM) comprising precipitation, temperature and carbon dioxide emissions. By importing the whole climate data set into the active map in DIVA-GIS, predictions regarding changes in climatic variables on the distributional patterns of focal species are possible. Ecological niche models were based on the 19 bioclimatic variables (table 1) in the WorldClim data set [Hijmans et al., 2005]. These variables are derived from region-specific monthly average minimum and maximum temperature (degrees Celsius) and monthly precipitation (millimetres) collated by Hijmans et al. [2005] from a variety of climatic records (including local, regional, national and global) dating from 1950 to 2000, with 1 km spatial resolution.

Table 1

BIOCLIM variables adopted from the WorldClim global climate database (http://www.worldclim.org/bioclim)

http://www.karger.com/WebMaterial/ShowPic/205921

The ‘predict’ function in DIVA-GIS was used to estimate the most suitable ecological niches of modern-day Chinese gibbons based on the BIOCLIM variables, with predictions ranging from ‘not suitable’ to ‘excellent’ suitability. Niche suitability is defined by the BIOCLIM variables using an algorithm within DIVA-GIS which assesses suitability on the basis of optimum climatic conditions derived from the BIOCLIM data. Further ENM analyses were undertaken to predict how these niches would vary in the future under changing climatic scenarios. The niche-modelling function allows mean temperature and precipitation levels to be altered and to predict the effect that such changes will have on the spatial distribution of focal species. Over the next 30 years, annual mean temperatures across China are likely to increase by approximately 0.71°C, and annual mean precipitation levels are likely to increase by approximately 8.4 mm across much of the country [Liu et al., 2010]. Under these predictions, the BIOCLIM variables were changed accordingly in DIVA-GIS, and maps were generated in order to show those regions of China in which gibbons may still occur in the future, notwithstanding other factors which are also likely to affect regional gibbon survival such as deforestation and confounding effects of human population expansion.

Results

Four maps were generated showing the following point locality information: fossil, historical, present-day, and a combined map illustrating distributional range shifts from the Pliocene to the present. Pliocene-Holocene gibbon fossils (74 records) are distributed from southernmost China to the Yangtze River delta in eastern China (fig. 1). This is congruent with the distribution of the Quaternary Stegodon-Ailuropoda fauna, of which gibbons are considered to represent a key component, across subtropical southern China in the formerly forested area south of the Qinling Mountains [Ciochon, 2010]. There are more gibbon fossil records from the south-western provinces of Yunnan (19 records), Guangxi (24 records) and Hainan (6 records) compared to more northern and eastern provinces (Guizhou, Guangdong, Hunan, Hubei, Chongqing, Fujian, Zhejiang, Jiangsu), but it is important to note that we cannot account for collection biases, nor can we account for identification problems. About 65% of the gibbon fossils were not identified to species, but 20 records were identified as N. concolor and 5 records were identified as H. leuconedys [formerly referred to as Bunopithecus hoolock in China]. This apparent abundance of N. concolor in the recent Chinese fossil record is supported by Yi’s [1986] analysis of fossil Chinese gibbon teeth, which noted a high resemblance between the majority of available fossil molars with comparative modern material of N. concolor. However, these identifications and studies are mostly based on older gibbon species concepts which assumed a much broader concept of N. concolor and did not recognize the validity of taxa such as N. hainanus and N. nasutus [Groves, 2001], which are now known to be the most divergent members of the genus Nomascus [Thinh et al., 2010]; this suggests that such identifications should be treated at the genus level only, and emphasizes the need for a modern re-examination of Chinese gibbon fossil material.

Fig. 1

Map of China showing the geographical distribution of gibbons during the Pliocene-Holocene.

http://www.karger.com/WebMaterial/ShowPic/205920

The distribution of gibbons during the Chinese historical period (AD 265–1945) ranged across southern China to the north as far as the Yangtze region (fig. 2). This is broadly congruent with the distribution of older Pliocene and Quaternary fossil gibbon records, and indicates that gibbons either remained widely distributed over southern China throughout Pleistocene-Holocene climatic cycles or were able to recolonize this region relatively rapidly following periods of adverse climate. The species identification of most of these historical records is unknown [van Gulik, 1967; Wen, 2009], so these data should be treated with some caution. The provinces with the highest numbers of historical gibbon records are Yunnan, Guangdong, Fujian and Hunan. Wen [2009] suggested that the provinces with the highest historical gibbon population densities were Guangdong and Fujian. Gao et al. [1981] also suggested that there were large populations of H. leuconedys and N. concolor in Yunnan, Guangdong and Guangxi provinces before the eighteenth century based on historical records.

Fig. 2

Map of China showing the geographical distribution of gibbons during the historical period (AD 265–1945).

http://www.karger.com/WebMaterial/ShowPic/205919

Today, gibbons are present only in the three south-western provinces of China: Yunnan, Guangxi and Hainan (fig. 3). Whilst the recent diversity of gibbon species in China is high, their density is low, with population estimates for most species numbering no more than 300 individuals, and with two species possibly already regionally extirpated [IUCN, 2011]. The greatest range shift in Chinese gibbon populations has therefore taken place between the late Holocene historical period, when gibbons were still distributed across much of southern China, and the modern era (AD 1945 onwards), by which time northern populations had disappeared and remnant populations were greatly reduced and restricted to the far south-west of the country, with this large-scale range contraction taking place during an interval when environmental conditions were generally stable in comparison to older Quaternary environmental fluctuations (fig. 4).

Fig. 3

Map of China showing the geographical distribution of gibbons during the modern period (AD 1945 to the present).

http://www.karger.com/WebMaterial/ShowPic/205918

Fig. 4

Map of China comparing the geographical distribution of gibbons during fossil, historical and modern periods.

http://www.karger.com/WebMaterial/ShowPic/205917

Habitat suitability across modern-day China was predicted collectively for Chinese gibbon species using modern-day environmental parameters associated with gibbon occurrence (fig. 5). This analysis indicates that the areas suitable for gibbons in Yunnan, Guangxi and Hainan are geographically restricted, with large parts of these provinces characterized by low-to-medium habitat suitability. The analysis was repeated using modern and historical records combined, to predict the maximum upper limit of gibbon species’ ranges under recent environmental conditions (fig. 6). Predictions indicate that the maximum range of gibbons both in the past and present falls outside the range of potentially suitable habitat, with much of their current and historical range characterized by low or medium habitat suitability. In particular, the northern (Shanxi, Shandong), north-western (Shaanxi), western (Sichuan) and south-western (Yunnan, Hainan) peripheral extents of historical/modern gibbon range are characterized by low-to-medium habitat suitability. Conversely, there are areas beyond modern gibbon ranges characterized by high-to-excellent habitat suitability, including parts of central China (Guangxi, Guizhou, Guangdong, Jiangxi, Fujian).

Fig. 5

Map of China showing current predicted habitat suitability for gibbons using ENM implemented via DIVA-GIS.

http://www.karger.com/WebMaterial/ShowPic/205916

Fig. 6

Map of China showing current predicted habitat suitability for gibbons based on both modern and historical data, using ENM implemented via DIVA-GIS.

http://www.karger.com/WebMaterial/ShowPic/205915

When annual mean temperature and precipitation are increased by +0.71°C and +8.4 mm, respectively, following the relatively conservative climatic predictions of Liu et al. [2010], the distribution of suitable habitats predicted for modern gibbons decreases even further (fig. 7). On the basis of environmental parameters associated with modern-day gibbon distribution alone, we would predict that in the next 30 years, the suitability of habitats for gibbons will downgrade by at least one class across south-western China, and Yunnan will be the only area to contain suitable habitats for gibbons. These findings have significant consequences for future gibbon conservation action plans, as well as the relative importance of different data sources in predicting habitat suitability.

Fig. 7

Map of China showing future predicted habitat suitability for gibbons following climate change, with conservative temperature and precipitation increased by 0.71°C and 8.4 mm/year, respectively.

http://www.karger.com/WebMaterial/ShowPic/205914

Discussion

The distribution of gibbons in China has changed dramatically since the Plio-Pleistocene, with the complete disappearance of northern populations such that gibbons are now restricted to small forest fragments in Yunnan, Guangxi and Hainan, and with several species either already regionally extirpated or on the verge of extinction. Gibbon distribution in China during the Quaternary is likely to have been affected by the major climatic and environmental fluctuations that occurred throughout this interval, as well as by other factors such as changes in the course of major rivers such as the Yangtze and Mekong due to tectonic activity [Jablonski and Chaplin, 2009]. Indeed, Jablonski et al. [2000] suggested that hominoids such as gibbons, with relatively long gestation times, long weaning periods, long interbirth intervals, lower intrinsic rates of population increase and preferences for higher-quality fruits from less seasonal environments, were likely to have been more vulnerable to environmental changes during the Quaternary than other primates. It is possible that finer-resolution temporal analysis (dependent upon better dating of fossil material than is currently available) may provide evidence of pre-Holocene gibbon range shifts across China in response to these environmental changes. However, our results demonstrate that the geographical distribution of gibbons was relatively stable across a wide area of southern China until the recent historical past, and that the most significant range reduction has been driven by human activity rather than older environmental change, a pattern comparable to that shown across recent centuries in China both by other primates [Zhang et al., 1989; Li et al., 2002] and also by a wide range of other large mammal species [Coggins, 2003; Elvin, 2004; Wen, 2009].

ENM based on modern-day gibbon distributional data suggests that gibbons are not currently distributed across the most optimal geographical areas in China as regards predicted habitat suitability. When historical records are also included in the analysis, it is evident that there are areas beyond current gibbon ranges, especially in central China, which afford potentially suitable habitats, further indicating that anthropogenic rather than environmental conditions have restricted the modern-day distribution of gibbons. ENM also suggests that predicted changes in China’s climate will result in the further contraction of Chinese gibbon ranges, and may lead to complete extirpation of gibbons in some areas.

It is worth noting that ENM, as a tool for predicting the impact of climate change on species ranges, has received some criticism on the basis that several other factors affect distribution, including species dispersal, biotic interactions, land use and topography [Pearson and Dawson, 2003; Guisan and Thuiller, 2005]. The use of the BIOCLIM algorithm within DIVA-GIS has also been criticized since it relies on presence-only data, whereas methods that employ presence-absence data (e.g. MAXENT, GARP) to predict species distributions may be more accurate [Elith et al., 2006]. Whilst it is undoubtedly preferable to incorporate absence data and invoke more sophisticated algorithms in ENM, generating meaningful absence data from both the Chinese historical and recent fossil records remains challenging in the face of complex biases from taphonomy, fossil-collecting biases in past data collection and interpretation across different regions; the use of DIVA-GIS in this study enables a first attempt at predicting potential species’ ranges and incorporating data from the past and present. Furthermore, as Elith et al. [2006] have pointed out, studies using presence-only data have been shown to be sufficiently accurate to be used in conservation planning, albeit using different predictive models [Pearce and Ferrier, 2000].

Notwithstanding the limitations of ENM, there is no doubt that the threat of climatically driven environmental change will be compounded if remaining gibbon habitats continue to be threatened by human-caused deforestation together with exploitation and other anthropogenic activities. Human population growth rates in Hainan, Yunnan and Guangxi, the three Chinese provinces that still contain native gibbon populations, increased by over 200, 125–150 and 125–150%, respectively, during the second half of the twentieth century, with concomitant increases in industrialization, and populations are predicted to continue growing into the future, with severe implications for persistence of natural habitats [Yang et al., 1987; Wang, 2000]. This problem may also be exacerbated by the possibility that some surviving Chinese gibbon populations, notably the last remaining population of Hainan gibbons in Bawangling National Nature Reserve, may already be persisting in suboptimal habitat fragments due to regional loss of more suitable forest environments and lack of habitat connectivity [Chan et al., 2005; Fellowes et al., 2008; Zhang et al., 2010].

However, a comparison of our ENM outputs with the extensive historical data set available for gibbon distribution across China over the last two millennia provides more room for hope, and also acts as a lesson about the importance of incorporating data from the past as well as the present in order to generate a more meaningful evidence base for understanding anthropogenic impacts on biodiversity [Sutherland et al., 2004; Jackson and Hobbs, 2009; Turvey, 2009]. Faunal and environmental data both suggest that the subtropical Oriental Realm and its associated mammal fauna extended as far north as the Qinling Mountains throughout the glacial-interglacial cycles of the Late Quaternary [Yang, 1986], and although some (often regional or local) relatively small-scale climatic fluctuations are known from the late Holocene of China, these are much less significant than either the large-scale shift from glacial to interglacial conditions at the Pleistocene-Holocene boundary or even other fluctuations that occurred during the early-middle Holocene [Tao et al., 2006; Zhao et al., 2007]. Indeed, records from the last two millennia almost certainly represent climatic conditions that are closely similar to those found today [Roberts, 1998]. Any changes during this period to the distributions of gibbon populations with a long evolutionary history in China [Chatterjee 2009; Thinh et al., 2010] are therefore almost certainly associated with past human activity rather than natural environmental change. Whereas ENM based on modern-day gibbon distributional data alone suggests that gibbons in China now occupy suboptimal habitats and face a serious threat from environmental change in the future, historical data instead demonstrate that under climatic conditions very close to those of the present day, gibbons were in fact widely distributed across a much wider area of southern China until the very recent past. This past distribution pattern would be unexpected if only data from the present were available for consideration. The current-day distribution of gibbons in China therefore represents merely their realized niche as a result of widespread recent anthropogenic habitat destruction across their original late Holocene range, and not their fundamental niche of actual environmental tolerances, so that conservation conclusions based on this current-day distribution alone will be artificially restrictive and pessimistic.

Whilst we acknowledge the potential limitations of ENM, it represents a useful starting place for mapping the potential range of a species under a climate change scenario, and here it has illustrated the importance of incorporating past as well as present-day data in predicting species’ tolerance to environmental change. Although the last surviving gibbon populations in China today are undeniably under extreme threat, with concerted conservation action it may still be possible to prevent their extinction even under future scenarios of climatically driven environmental change. We highlight this mismatch between conclusions derived from modern-day data and historical data as a key finding from our study, and emphasize the need for further, quantitative analysis of the extensive Chinese historical record, which represents an invaluable but currently underutilized tool for conservation research.

Acknowledgments

We are grateful to Nina Jablonski and George Chaplin for contributing gibbon fossil data and Wilfried Thuiller for making useful comments about ENM and BIOCLIM in an earlier version of this paper.


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  40. Schipper J, et al (2008). The status of the world’s land and marine mammals: diversity, threat, and knowledge. Science 322: 225–230.
  41. Shen D, Varis O (2001). Climate change in China. Ambio 30: 381–383.
  42. Stigall AL, Lieberman BS (2006). Quantitative palaeobiogeography: GIS, phylogenetic biogeographical analysis, and conservation insights. Journal of Biogeography 33: 2051–2060.
    External Resources
  43. Sutherland WJ, Pullin AS, Dolman PM, Knight TM (2004). The need for evidence-based conservation. Trends in Ecology and Evolution 19: 305–308.
  44. Tao J, Chen M, Xu S (2006). A Holocene environmental record from the southern Yangtze River delta, eastern China. Palaeogeography, Palaeoclimatology, Palaeoecology 230: 204–229.
    External Resources
  45. Thinh VN, Mootnick AR, Geissmann T, Li M, Ziegler T, Agil M, Moisson P, Nadler T, Walter L, Roos C (2010). Mitochondrial evidence for multiple radiations in the evolutionary history of small apes. BMC Evolutionary Biology 10: 74.
  46. Thorn JS, Nijman V, Smith D, Nekaris KAI (2009). Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions 15: 289–298.
    External Resources
  47. Turvey ST (2009). Holocene Extinctions. Oxford, Oxford University Press.
  48. Turvey ST, Barrett LA, Hart T, Collen B, Hao Y, Zhang L, Zhang X, Wang X, Huang Y, Zhou K, Wang D (2010). Spatial and temporal extinction dynamics in a freshwater cetacean. Proceedings of the Royal Society B: Biological Sciences 277: 3139–3147.
    External Resources
  49. Van Gulik RH (1967). The Gibbon in China: An Essay in Chinese Animal Lore. Leiden, Brill.
  50. Waltari E, Guralnick RP (2009). Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges. Journal of Biogeography 36: 148–161.
    External Resources
  51. Wang G (2000). The distribution of China’s population and its changes. In The Changing Population of China (Peng X, Gao Z, eds.), pp 11–19. Oxford, Blackwell.
  52. Wei P (1988). Through historical records and ancient writings in search of the giant panda. Journal of the Hong Kong Branch of the Royal Asiatic Society 28: 34–43.
  53. Wen RS (2009). The Distributions and Changes of Rare Wild Animals in China. Chongqing, Chongqing Science and Technology Press.
  54. Yang D, Liu L, Chen X, Speller CF (2008). Wild or domesticated: DNA analysis of ancient water buffalo remains from north China. Journal of Archaeological Science 35: 2778–2785.
    External Resources
  55. Yang D, Zhang J, Li C (1987). Preliminary survey on the population and distribution of gibbons in Yunnan Province. Primates 28: 547–549.
    External Resources
  56. Yang Z (1986). The Geology of China. Oxford, Clarendon Press.
  57. Yi Y (1986). Initial investigation on gibbon fossils found in China during Pleistocene. Acta Anthropologica Sinica 5: 208–219.
  58. Zhang J, Lin Z (1992). Climate of China. Shanghai, Wiley & Sons/Shanghai Scientific and Technical Publishers.
  59. Zhang M, Fellowes JR, Jiang X, Wang W, Chan BPL, Ren G, Zhu J (2010). Degradation of forest habitat in Hainan, China, 1991–2008: conservation implications for Hainan gibbon (Nomascus hainanus).Biological Conservation 143: 1397–1404.
    External Resources
  60. Zhang Y, Quan G, Lin Y, Southwick C (1989). Extinction of rhesus monkeys (Macaca mulatta) in Xinglung, North China. International Journal of Primatology 10: 375–381.
  61. Zhao Y, Hölzer A, Yu Z (2007). Late Holocene natural and human-induced environmental change reconstructed from peat records in eastern central China. Radiocarbon 49: 789–798.

Author Contacts

H.J. Chatterjee, Research Department of Genetics,

Evolution and Environment

University College London, Gower Street

London WC1E 6BT (UK)

E-Mail h.chatterjee@ucl.ac.uk


Article / Publication Details

First-Page Preview
Abstract of Original Article

Received: October 10, 2011
Accepted: August 14, 2012
Published online: October 02, 2012
Issue release date: December 2012

Number of Print Pages: 15
Number of Figures: 7
Number of Tables: 1

ISSN: 0015-5713 (Print)
eISSN: 1421-9980 (Online)

For additional information: http://www.karger.com/FPR


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  40. Schipper J, et al (2008). The status of the world’s land and marine mammals: diversity, threat, and knowledge. Science 322: 225–230.
  41. Shen D, Varis O (2001). Climate change in China. Ambio 30: 381–383.
  42. Stigall AL, Lieberman BS (2006). Quantitative palaeobiogeography: GIS, phylogenetic biogeographical analysis, and conservation insights. Journal of Biogeography 33: 2051–2060.
    External Resources
  43. Sutherland WJ, Pullin AS, Dolman PM, Knight TM (2004). The need for evidence-based conservation. Trends in Ecology and Evolution 19: 305–308.
  44. Tao J, Chen M, Xu S (2006). A Holocene environmental record from the southern Yangtze River delta, eastern China. Palaeogeography, Palaeoclimatology, Palaeoecology 230: 204–229.
    External Resources
  45. Thinh VN, Mootnick AR, Geissmann T, Li M, Ziegler T, Agil M, Moisson P, Nadler T, Walter L, Roos C (2010). Mitochondrial evidence for multiple radiations in the evolutionary history of small apes. BMC Evolutionary Biology 10: 74.
  46. Thorn JS, Nijman V, Smith D, Nekaris KAI (2009). Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus). Diversity and Distributions 15: 289–298.
    External Resources
  47. Turvey ST (2009). Holocene Extinctions. Oxford, Oxford University Press.
  48. Turvey ST, Barrett LA, Hart T, Collen B, Hao Y, Zhang L, Zhang X, Wang X, Huang Y, Zhou K, Wang D (2010). Spatial and temporal extinction dynamics in a freshwater cetacean. Proceedings of the Royal Society B: Biological Sciences 277: 3139–3147.
    External Resources
  49. Van Gulik RH (1967). The Gibbon in China: An Essay in Chinese Animal Lore. Leiden, Brill.
  50. Waltari E, Guralnick RP (2009). Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges. Journal of Biogeography 36: 148–161.
    External Resources
  51. Wang G (2000). The distribution of China’s population and its changes. In The Changing Population of China (Peng X, Gao Z, eds.), pp 11–19. Oxford, Blackwell.
  52. Wei P (1988). Through historical records and ancient writings in search of the giant panda. Journal of the Hong Kong Branch of the Royal Asiatic Society 28: 34–43.
  53. Wen RS (2009). The Distributions and Changes of Rare Wild Animals in China. Chongqing, Chongqing Science and Technology Press.
  54. Yang D, Liu L, Chen X, Speller CF (2008). Wild or domesticated: DNA analysis of ancient water buffalo remains from north China. Journal of Archaeological Science 35: 2778–2785.
    External Resources
  55. Yang D, Zhang J, Li C (1987). Preliminary survey on the population and distribution of gibbons in Yunnan Province. Primates 28: 547–549.
    External Resources
  56. Yang Z (1986). The Geology of China. Oxford, Clarendon Press.
  57. Yi Y (1986). Initial investigation on gibbon fossils found in China during Pleistocene. Acta Anthropologica Sinica 5: 208–219.
  58. Zhang J, Lin Z (1992). Climate of China. Shanghai, Wiley & Sons/Shanghai Scientific and Technical Publishers.
  59. Zhang M, Fellowes JR, Jiang X, Wang W, Chan BPL, Ren G, Zhu J (2010). Degradation of forest habitat in Hainan, China, 1991–2008: conservation implications for Hainan gibbon (Nomascus hainanus).Biological Conservation 143: 1397–1404.
    External Resources
  60. Zhang Y, Quan G, Lin Y, Southwick C (1989). Extinction of rhesus monkeys (Macaca mulatta) in Xinglung, North China. International Journal of Primatology 10: 375–381.
  61. Zhao Y, Hölzer A, Yu Z (2007). Late Holocene natural and human-induced environmental change reconstructed from peat records in eastern central China. Radiocarbon 49: 789–798.
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