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An Assessment of the Distribution and Conservation Status of Hornbill Species in Thailand

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An Assessment of the Distribution and Conservation Status of Hornbill Species in Thailand An assessment of the distribution and conservation status of hornbill species in Thailand Y ONGYUT T RISURAT,VIJAK C HIMCHOME,ANAK P ATTANAVIBOOL S ITTHICHAI J INAMOY,SIRIPORN T HONGAREE,BUDSABONG K ANCHANASAKHA S AKSIT S IMCHAROEN,KRIANGSAK S RIBUAROD,NARONG M AHANNOP and P ILAI P OONSWAD Abstract Many hornbill species in Thailand are categorized Introduction as Endangered or Critically Endangered on the IUCN 54 Red List. The objectives of this research were to predict he Asian hornbills, family Bucerotidae, comprise 2001 hornbill distributions in Thailand and to assess the national Tspecies (Kemp, ). They are primarily frugivorous, fi conservation status of the species using extent of occur- eating a variety of fruits, with gs predominant in their diet, rence. We employed maximum entropy modelling, using 10 but they also consume a diversity of animal prey (Poonswad, 1998 environmental variables that were believed to directly or ). They play an important role in seed dispersal in ‘ indirectly influence hornbill distributions across Thailand, tropical forests and have been referred to as the farmers ’ ’ 2007 to predict the habitats potentially suitable for 10 of the of the forest (Kinnaird & O Brien, ). The decline of ff country’s 13 hornbill species. Data on the presence of hornbills has a ected the dispersal and recruitment of hornbills were gathered from the Thailand Hornbill Project large-seeded tree species in logged forests in the foothills 2009 and additional field surveys in protected area complexes of the Indian Eastern Himalayas (Sethi & Howe, ) and during 2004–2006. The results indicated that patch size is monsoon evergreen forest in Khao Yai, Thailand (Kitamura 2004 the most important factor affecting distribution, followed by et al., ). Hornbills are useful indicators of forest latitude, ecoregion and distance to villages. All hornbill condition and human disturbance because they require species were predicted to occur primarily in intact protected large tracts of forest with large fruiting trees for feeding and 2005 ’ 2007 area complexes. The total extent of all hornbill habitats nesting (Poonswad et al., ; Kinnaird & O Brien, ). covers 9.3% of the country’s land area. Seven of the The accelerated loss and fragmentation of Asian forest in 1990 10 modelled species are at risk and the current distri- the s, followed by hunting, are the most commonly bution pattern is expected to reflect stochastic extinctions cited reasons for hornbills being threatened (Poonswad 2005 ’ 2007 because of small population size. We recommend that the et al., ; Kinnaird & O Brien, ). Thailand has lost as 70 2007 conservation status of Austen’s brown hornbill Anorrhinus much as % of its original forest cover (DNP, ). fi fl austeni and Tickell’s brown hornbill Anorrhinus tickelli Landscape patterns are signi cant factors in uencing the ’ 1998 should be changed from Vulnerable to Endangered. The distribution of hornbills (O Brien et al., ; Raman & 2003 2004 model identified five protected area complexes as hornbill Mudappa, ; Pattanavibool et al., ; Sitompul et al., 2004 ’ 2007 hotspots in Thailand. These findings will help guide ; Kinnaird & O Brien, ). Isolation of suitable food conservation management. patches prevents food tracking behaviour, and adversely affects populations of avian frugivores through starvation, Keywords Anorrhinus, distribution, hornbill, Maxent, and food plants through interruption of seed dispersal Thailand (Lehouck et al., 2009). Sitompul et al. (2004) indicated that hornbills are more vulnerable to stochastic effects and patch size than overall resource availability. O’Brien et al. (1998) found that the Sumba hornbill Aceros everetti was rare or 2 absent in forest patches , 10 km . Thailand is home to 13 species and one subspecies of YONGYUT TRISURAT (Corresponding author) and VIJAK CHIMCHOME Faculty of Forestry and Center for Advanced Studies in Tropical Natural Resources, hornbill and Thai researchers have conducted long-term Kasetsart University, Bangkok 10900, Thailand. E-mail ff[email protected] studies of hornbills (Poonswad, 1998; THP, 2009). All ANAK PATTANAVIBOOL Wildlife Conservation Society, Thailand Program, species except the oriental pied hornbill Anthracoceros Nontaburi, Thailand albirostris are categorized nationally as threatened species SITTHICHAI JINAMOY and PILAI POONSWAD Department of Microbiology, Mahidol (ONEP, 2007) but none are endemic to Thailand (Kinnaird University, Bangkok, Thailand &O’Brien, 2007). Estimation of changes in the distribution SIRIPORN THONGAREE,BUDSABONG KANCHANASAKHA,SAKSIT SIMCHAROEN, of hornbills in Thailand (Poonswad, 1998) suggests that KRIANGSAK SRIBUAROD and NARONG MAHANNOP Department of National Park, 32 Wildlife and Plant Conservation, Bangkok, Thailand c. % of the land area contains potentially suitable habitats Received 27 December 2010. Revision requested 12 May 2011. for hornbills but this is less than that of earlier assessments Accepted 1 June 2011. First published online 9 May 2013. by Lekagul & Cronin (1974). © 2013 Fauna & Flora International, Oryx, 47(3), 441–450 doi:10.1017/S0030605311001128 Downloaded from https://www.cambridge.org/core. IP address: 170.106.202.58, on 28 Sep 2021 at 06:14:33, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0030605311001128 442 Y. Trisurat et al. There are a number of modelling methods available resolution of the topographic maps and the coarse for predicting the potential distribution of species. These resolution of the climatic variables, and corresponds to the models are based on the assumption that the relationship minimum mapping unit of the vegetation type map. between a given pattern of interest (e.g. species abundance We constructed a matrix of correlations between all or presence/absence) and a set of factors assumed to control possible pairs of variables. Pearson’s correlations indicated it can be quantified (Phillips et al., 2006; Trisurat & that all pairs had coefficients , 0.70. Thus, there do not Toxopeus, 2011). Recent advances employing geographical appear to be problems with multicollinearity (Graham et al., information systems (GIS) allow correlative modelling of 2008), which can otherwise result in model overfitting species’ distributions for large geographical areas, which is (Peterson et al., 2007), and therefore all 10 variables were useful when detailed information about the natural history used for modelling species distributions. of species is lacking (Anderson et al., 2002; Trisurat & Toxopeus, 2011). The objectives of our research were to predict hornbill distributions in Thailand and assess their Species distribution modelling current conservation status based on extent of occurrence derived from GIS-based habitat modelling. The processes for mapping distributions comprised: (1) collection of observation points, (2) generation of distri- butions, (3) assessment of status, and (4) determination Methods of priority areas for hornbill conservation. We collected species presence points from the Thailand Hornbill Project Study area and additional field surveys during 2004–2006. Since the 1980s the Project has regularly collected data on sightings We assessed hornbill distributions at two levels: the 2 and vocal detections of hornbills (THP, 2009) but geo- entire 513,200 km of Thailand, and the 12 protected area 2 graphical locations have only been recorded since 2000. The complexes comprising a total of 65,528 km that potentially 2004–2006 data were jointly collected by the Project and contain hornbill habitat. Six additional complexes in the Wildlife Conservation Society Thailand. Survey teams Thailand have no records of hornbills in the last 2 decades comprising 3–4 people walked along wildlife trails or (Poonswad, 1998) and the remaining forest cover in these patrol routes, recording hornbill locations using a global complexes is small and severely fragmented. positioning system and topographic maps. Although we initially aimed to model the distributions of 13 Data collection all hornbill species in Thailand, we only had adequate records (. 20) for modelling for 10 of the species (Table 1). We collected data on four abiotic factors (altitude, slope, From the available species modelling techniques we selected latitude and annual rainfall), four biotic factors (ecoregion maximum entropy modelling (Phillips et al., 2006) because type, vegetation type, patch size and distance to forest patch it was specifically developed to model species distributions 2 . 50 km , which included evergreen, deciduous or mixed with presence-only data (Phillips et al., 2006), outperforms forest, disturbed forest and forest plantation) and two most other modelling techniques (Tognelli et al., 2009), anthropogenic factors (distance to village and distance to is least affected by geo-referencing errors (Graham et al., road) that have been identified as directly or indirectly 2008), and performs best when few presence records are affecting patterns of abundance and distribution of hornbills available (Wisz et al., 2008). (O’Brien et al., 1998; Poonswad, 1998; Sitompul et al., 2004; The occurrence data for each species was randomly Kinnaird & O’Brien, 2007). Vegetation types were derived divided into two datasets. Seventy-five percent (training from a 2006 1 : 50,000 forest type map (DNP, 2007). Patch data) were used to generate distribution models and 25% size and distance to large forest patch were derived from (test data) were kept as independent data to test the
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