Abstract:Effects of anthropogenic disturbance on group densities of Thomas' langurs (Presbytis thomasi) within a lowland tropical forest, north Sumatra http://researchonline.ljmu.ac.uk/id/eprint/18224/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively.
“…For this reason, we used the densities from the ASCR before the divisions for the population size calculation and correlation analyses with habitat characteristics. The finding that the D of ASCR before division is more realistic than that of ASCR after division was similar to the findings of previous studies for lar gibbon ( Hylobates lar ) and siamang ( Symphalangus syndactylus ) in north Sumatra ( Hankinson et al 2021 ; personal communication, Hankinson 2022), but not for Thomas' langurs ( Presbytis thomassi) ( Hankinson et al 2022 ). By contrast, in accordance with the instruction on the manual web-page of ASCR to divide the D by the number of survey days and p(1) , the langur group densities appeared to be realistic and comparable with the results of a previous studies ( Hankinson et al 2022 ).…”
Section: Discussionsupporting
confidence: 89%
“…The finding that the D of ASCR before division is more realistic than that of ASCR after division was similar to the findings of previous studies for lar gibbon ( Hylobates lar ) and siamang ( Symphalangus syndactylus ) in north Sumatra ( Hankinson et al 2021 ; personal communication, Hankinson 2022), but not for Thomas' langurs ( Presbytis thomassi) ( Hankinson et al 2022 ). By contrast, in accordance with the instruction on the manual web-page of ASCR to divide the D by the number of survey days and p(1) , the langur group densities appeared to be realistic and comparable with the results of a previous studies ( Hankinson et al 2022 ). This study indicates that the ASCR method is a useful modelling tool for calculating gibbon or primate density, based on calls, although the steps to divide the D by the number of survey days and p(1) may give different results in different species at different study sites.…”
Section: Discussionsupporting
confidence: 89%
“…The gibbon group density data were calculated per array using the standard triangulation calculation ( Brockelman and Ali 1987 , Nijman 2004 , Cheyne et al 2008 , Hamard et al 2010 ) and an ASCR programme ( Stevenson et al 2021 ). However, on the basis of cases reported in previous studies ( Hankinson et al 2022 ), we used two alternative calculation methods for the ASCR calculation, which are explained in the Acoustic spatial capture-recapture subsection . As a result, this study compared the gibbon group densities obtained from three methods using paired t tests to analyse the differences between the methods ( Hankinson et al 2021 ).…”
Section: Methodsmentioning
confidence: 99%
“…The D estimated from the ASCR programme should be divided by the number of survey days and then by the daily calling probability p(1) to obtain the group density in a site ( Hankinson et al 2022 , Jones-Todd 2022 ). However, these steps were not applied for calculating the densities of Hylobates lar and Symphalangus syndactylus in North Sumatra in a previous study ( Hankinson et al 2021 ).…”
The Javan gibbon (Hylobates moloch) is endemic to the island of Java and its distribution is restricted from the western tip of Java to the Dieng Mountains in Central Java. Unlike the other known habitats that hold a large population of Javan gibbons, the Dieng Mountains have not been protected and experience various threats. This study, which was conducted in 2018 and 2021, aimed to provide an update of the current density and population size of Javan gibbons in Dieng after the most recent study in 2010 and to investigate their relationships with habitat characteristics (vegetation and elevation). The triangulation method and a new acoustic spatial capture-recapture method were used to estimate group density. A new approach for extrapolation, based on the habitat suitability model, was also developed to calculate population size. The results show that the Javan gibbon population in the Dieng Mountains has most likely increased. The mean group density in each habitat type was high: 2.15 groups/km2 in the low suitable habitat and 5.55 groups/km2 in the high suitable habitat. The mean group size (3.95 groups/km2, n = 20) was higher than those reported in previous studies. The overall population size was estimated to be 1092 gibbons. This population increase might indicate the success of conservation efforts during the last decade. However, more effort should be made to ensure the long-term future of this threatened species. Although the density significantly differed between habitat suitability types, it was not influenced by the vegetation structure or elevation. A combination of multiple variables will probably have a greater effect on density variation.
“…For this reason, we used the densities from the ASCR before the divisions for the population size calculation and correlation analyses with habitat characteristics. The finding that the D of ASCR before division is more realistic than that of ASCR after division was similar to the findings of previous studies for lar gibbon ( Hylobates lar ) and siamang ( Symphalangus syndactylus ) in north Sumatra ( Hankinson et al 2021 ; personal communication, Hankinson 2022), but not for Thomas' langurs ( Presbytis thomassi) ( Hankinson et al 2022 ). By contrast, in accordance with the instruction on the manual web-page of ASCR to divide the D by the number of survey days and p(1) , the langur group densities appeared to be realistic and comparable with the results of a previous studies ( Hankinson et al 2022 ).…”
Section: Discussionsupporting
confidence: 89%
“…The finding that the D of ASCR before division is more realistic than that of ASCR after division was similar to the findings of previous studies for lar gibbon ( Hylobates lar ) and siamang ( Symphalangus syndactylus ) in north Sumatra ( Hankinson et al 2021 ; personal communication, Hankinson 2022), but not for Thomas' langurs ( Presbytis thomassi) ( Hankinson et al 2022 ). By contrast, in accordance with the instruction on the manual web-page of ASCR to divide the D by the number of survey days and p(1) , the langur group densities appeared to be realistic and comparable with the results of a previous studies ( Hankinson et al 2022 ). This study indicates that the ASCR method is a useful modelling tool for calculating gibbon or primate density, based on calls, although the steps to divide the D by the number of survey days and p(1) may give different results in different species at different study sites.…”
Section: Discussionsupporting
confidence: 89%
“…The gibbon group density data were calculated per array using the standard triangulation calculation ( Brockelman and Ali 1987 , Nijman 2004 , Cheyne et al 2008 , Hamard et al 2010 ) and an ASCR programme ( Stevenson et al 2021 ). However, on the basis of cases reported in previous studies ( Hankinson et al 2022 ), we used two alternative calculation methods for the ASCR calculation, which are explained in the Acoustic spatial capture-recapture subsection . As a result, this study compared the gibbon group densities obtained from three methods using paired t tests to analyse the differences between the methods ( Hankinson et al 2021 ).…”
Section: Methodsmentioning
confidence: 99%
“…The D estimated from the ASCR programme should be divided by the number of survey days and then by the daily calling probability p(1) to obtain the group density in a site ( Hankinson et al 2022 , Jones-Todd 2022 ). However, these steps were not applied for calculating the densities of Hylobates lar and Symphalangus syndactylus in North Sumatra in a previous study ( Hankinson et al 2021 ).…”
The Javan gibbon (Hylobates moloch) is endemic to the island of Java and its distribution is restricted from the western tip of Java to the Dieng Mountains in Central Java. Unlike the other known habitats that hold a large population of Javan gibbons, the Dieng Mountains have not been protected and experience various threats. This study, which was conducted in 2018 and 2021, aimed to provide an update of the current density and population size of Javan gibbons in Dieng after the most recent study in 2010 and to investigate their relationships with habitat characteristics (vegetation and elevation). The triangulation method and a new acoustic spatial capture-recapture method were used to estimate group density. A new approach for extrapolation, based on the habitat suitability model, was also developed to calculate population size. The results show that the Javan gibbon population in the Dieng Mountains has most likely increased. The mean group density in each habitat type was high: 2.15 groups/km2 in the low suitable habitat and 5.55 groups/km2 in the high suitable habitat. The mean group size (3.95 groups/km2, n = 20) was higher than those reported in previous studies. The overall population size was estimated to be 1092 gibbons. This population increase might indicate the success of conservation efforts during the last decade. However, more effort should be made to ensure the long-term future of this threatened species. Although the density significantly differed between habitat suitability types, it was not influenced by the vegetation structure or elevation. A combination of multiple variables will probably have a greater effect on density variation.
“…Subsistence and smallholder agriculture are the predominant land uses outside the protected forest in Aras Napal, whereas the area to the north of the village comprises larger commercial rubber and oil palm plantations. Except for a few primate studies (Harrison et al, 2020; Roth et al, 2020; Hankinson et al, 2021, 2022), there are no published data on mammals in Sikundur. Fig.…”
Species–environment relationships are often studied at large spatial scales, but effective conservation requires an understanding of local-scale environmental drivers and pressures. Widespread degradation and fragmentation of forests have increased the proportion of tropical mammal habitat that is affected by edge effects. Edge effects include greater exposure to anthropogenic disturbance and abiotic changes that synergistically influence how well populations can cope with climate change. We investigated relationships between distance to the forest edge, forest structure, microclimate and terrestrial mammal detections in a selectively logged forest at the boundary of Gunung Leuser National Park in Sumatra, Indonesia. We collected mammal detection data from motion-activated camera traps, microclimate data from automated climate data loggers and forest structure data from vegetation plots. Daily mean and maximum temperatures significantly decreased with distance from the forest edge, whereas tree height and minimum temperature increased. Mammal diversity was lower at the forest edge compared to the interior. Mammals were detected less frequently at the forest edge, although this relationship varied between mammal orders. Mammal detections were best explained by temperature, tree height and tree diameter at breast height. These results demonstrate that abiotic changes in forests brought on by edge effects have negative impacts on mammals, but these effects vary between mammal taxa because of differing sensitivities to human disturbance. Our findings highlight the importance of considering local-scale environmental drivers in determining species–environment relationships to identify key habitat features such as microclimate refuges that should be prioritized in ecosystem management.
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