The Habitat Suitability Modelling of Rhinoceros Hornbills (Buceros rhinoceros) in Java Island, Indonesia
Article Sidebar
Accepted
5 December 2023
Published
30 May 2024
Keywords:
-
Rhinoceros hornbills, Java Island habitat suitability, presence data, environmental variables
Abstract
Rhinoceros hornbills (Buceros rhinoceros) are a bird species belonging to the Bucerotidae family, which is vulnerable based on the IUCN red list of species. This is due to habitat fragmentation, which reduced the Rhinoceros hornbill habitat on Java. Efforts and strategies are needed to maintain Rhinoceros hornbill habitats. Information on the suitability of the Rhinoceros hornbill habitat on Java Island is required to develop a Rhinoceros hornbill conservation strategy. This study aimed to determine a habitat suitability model that produces the highest accuracy, analyze hornbill habitat suitability, and identify environmental variables that affect the existence of rhinoceros hornbills. Habitat suitability models were processed using three algorithms: random forest, support vector regression, and MaxEnt. The data used to model habitat suitability were presence and environmental variables. The model was evaluated using various accuracy measures, namely overall accuracy, sensitivity (sn), specificity (sp), Area Under Curve (AUC), and kappa coefficient. The results
of model processing showed that the random forest algorithm produced the highest average accuracy of 0.74. The most important environmental variables for the habitat suitability model were the distance from the road (16.62%), distance from the forest (12.73%), and land cover (12.47%). The habitat suitability model was divided into three classes: low suitability, covering 75,048 km2 (55.94%); medium suitability, covering 52,911 km2 (39.44%); and high suitability, covering 6,213 km2 (4.63%). The results of the habitat suitability model showed that the habitat suitability class was the smallest in the area.
References
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Berg CC, Corner EJ. 2005. Moraceae: Ficeae. Flora Malesiana – Series 1, Spermatophyta. 17: 1–702.
Bibby C, Jones M, Marsden, S. 2000. Survei Burung. SMKG Mardi Yuana. Bogor
Cohen J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement. 20(1): 37 – 46. doi:10.1177/001316446002000104.
Condro AD. 2020. Dinamika distribusi spasial primata: Perubahan iklim dan impilkasinya terhadap pengelolaan konservasi [tesis]. Bogor (ID): Institut Pertanian Bogor.
Congalton RG, Green K. 1999. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, Florida (US): CRC Press, Inc
Cutler DR, Edwards Jr TC, K.H. Beard KH, Cutler A, Hess KT, Gibson J, Lawler JJ. 2007. Random forests for classification in ecology. Ecology. 88(11): 2783–2792. doi:10.1890/07-0539.1
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Ghozali I. 2009. Aplikasi Analisis Multivarite dengan SPSS, Cetakan Keempat. Semarang (ID) : Badan Penerbit Universitas Diponegoro.
Jarulis. 2019. Karakteristik Marfologi dan Genetik Burung Rangkong (Aves: Bucerotidae) serta penyebarannya di Indonesia [disertasi]. Bogor (ID): Institut Pertanian Bogor.
Johns AD. 1988. The use primary and selectively logged rainforest by Malaysian Hornbills (Bucerotidae) and Implications for their Conservation. Biological Conservation. 40(1): 179 -190.
Kamal S, Agustina E, Azhari. 2018. Populasi rangkong papan (Buceros bicornis) di ekosistem Tahura Pocut Meurah Intan Provinsi Aceh. Jurnal Biologi. 14(1): 10-19.
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Kutner MH, Nachtsheim CJ, Neter J, Li W. 2005. Applied Linear Statistical Models. 5th Edition. New York(US): McGraw-Hill/Irwin.
Liang H, Guoa Z, Wua J, Chena Z. 2020. GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression. Advanses in Space Research. 481-493.
Liaw A, Wiener M. 2002. Classification and Regression by randomForest. R News. 2: 18–22.
Lobo JM, Jimenez-Valverde A, Real R. 2008. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 17: 145 – 151. doi:10.1111/j.1466-8238.2007.00358.x.
Hadiprakarsa Y, Kinnaird MF. 2005. Foraging characteristics of an assemblage of Four Sumatran hornbill species. Bird Conservation International. 14:S53-S62-S53-S62.
Hadiprakarsa Y, Winarni NL. 2007. Fragmentasi hutan di Lampung, Sumatera vs burung rangkong: Mampukah burung rangkong bertahan hidup? Jurnal Indonesian Ornithologists’ Union (IdOU). 5 (1): 94―102.
Hadiprakarsa Y. 2008. Forest patch occupancy by sumatran hornbills in a fragmented landscape of southern sumatra, Indonesia [tesis]. Georgia : The University of Georgiax
Hijmans RJ, Phillips S, Leathwick J, Elith J. 2015. Dismo: Species Distribution Modeling. R Package Version 1.0-12 [internet]. [diakses 2021 Jul 14]. Tersedia pada: http://CRAN.R-project.org/package=dismo.
Hastie T, Tibshirani R, Friedman, J. 2009. The elements of statistical learning: Data mining, inference, and prediction (2nd ed., Vol. 1). New York (NY): Springer series in statistics New York. doi: 10.1007/978-0-387-84858-7.
Hidayat RA, Febriani N, Hanif M, Rahman H. 2020. Modeling of conservation priority the Helmeted Hornbil (Rhinoplax vigil) in Silokek Geopark Area, West Sumatera. doi:10.20944/preprints202009.0676.v1.
Hidayat RZ, Febriani N. 2021. Pemodelan probabilitas sebaran habitat untuk menentukan kawasan prioritas konservasi burung rangkong gading (rhinoplax vigil) di Geopark Silokek, Kabupaten Sijunjung. Konservasi Hayati.1 (1): 35-43.
Kutner MH, Nachtsheim CJ, Neter J, Li W. 2005. Applied Linear Statistical Models. 5th Edition. New York: McGraw-Hill/Irwin.
Liaw A, Wiener M. 2002. Classification and Regression by randomForest. R News. 2: 18–22.
Mackinnon J, Phillips K, Balen BV. 2010. Burung-Burung di Sumatera, Jawa, Bali, dan Kalimantan (Termasuk Sabah, Serawak, dan Brunei Darussalam). Bogor (ID): Burung Indonesia
Mercadier M, Lardy JP. 2019. Credit Spread Approximation and Improvement Using Random Forest Regression. European Journal of Operational Research. 351-365.
Meyer D. 2012. Support Vector Machine, The interface to libsvm in package e1071. Austria: FH Technikum Wien.
Nugraha CA. 2015. Pemodelan Spasial Kesesuaian Habitat Elang Jawa (Nisaetus bartelsi Stresemann, 1924) di Taman Nasional Gunung Halimun Salak [tesis]. Bogor (ID): Institut Pertanian Bogor.
Pramana GTS, Prasetyo LB, Iskandar E. 2023. The habitat suitability modelling of dare monkey (Macaca maura) in Bantimurung Bulusaraung National Park, South Sulawesi. Journal of Natural Resources and Environmental Management. 13(1): 57–67. doi:10.29244/jpsl.13.1.57–67.
Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling. 190(3-4): 231–259. doi:10.1016/j.ecolm odel.2005.03.026.
Pearson RG, Dawson TP. 2003. Predicting the impacts of climate change on the distribution of species: Are bioclimate envelope models useful? Global Ecology and Biogeography. 12: 361-371. doi:10.1046/j.1466-822X.2003.00042.x.
Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT. 2007. Predicting species distributions from small numbers of occurence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography. 34: 102–117.
Pudyatmoko S, Djuwantoko, Sabarno Y. 2007. Evidence of banteng (Bos javanicus) decline in Baluran National Park, Indonesia. Journal of Biological Sciences. 7(6): 854– 859. doi:10.3923/jbs.2007.854.859.
Rahman H. (2020). Spatial Assessment of Landscape Structure Changes an Ecological Connectivity in Pariaman. Journal of Remote Sensing GIS dan Technology. 6(1): 10-22.
Sodik M, Pudyatmoko S, Yuwono PSH, Imron MA. 2019. Okupansi Kukang Jawa (Nycticebus javanicus E. Geoffroy 1812) di Hutan Tropis Dataran Rendah di Kemuning, Bejen, Temanggung, Jawa Tengah. Jurnal Ilmu Lingkungan. 13: 15-27. doi:10.22146/jik.46141.
Strobl C, Boulesteix L, Zeileis A, Hothorn T. 2007. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinf, 8(1):25. doi:10.1186/1471-2105-8-25
Sunaryo S, Setiawan S, Siagian TH. 2015. Mengatasi Masalah Multikolinearitas dan Outlier dengan Pendekatan ROBPCA (Studi Kasus Analisis Regresi Angka Kematian Bayi di Jawa Timur). Jurnal Matematika, Sains, dan Teknologi. 12(1): 1-10.
Supriyadi R, Gata W, Maulidah N, Fauzi A. 2020. Penerapan algoritma random forest untuk menentukan kualitas anggur merah. Jurnal Ilmiah Ekonomi dan Bisnis. 13(2): 67 – 75.
Syechalad, Muhammad N. 2009. Perkebunan dalam Kajian Sosial Ekonomi. Banda Aceh (ID): Yayasan PENA.
Trainor C, Lesmana D, Gatur A. 2000. Importance of forest in the west side of Timor land-First study of biodiversity and socio-economic information in Timor island of Nusa Tenggara Timur. (Rep. No. 13). PKA/Birdlife International/WWF, Bogor.
Anggriawan V, Hariyadi B, Muswita. 2015. Keanekaragaman jenis rangkong dan tumbuhan pakannya di Harapan Rainforest Jambi. Biospecies. 8(2):73-79.
Allouche O, Tsoar A, Kadmon R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43: 1223 – 1232. doi:10.1111/j.1365-2664.2006.01214.x.
BirdLife International. 2018. Rhyticeros undulatus. The IUCN Red List of Threatened Species 2018e.T22682528A132400385 [internet]. [diakses 2021 Jan 5]. Tersedia pada: http://dx.doi.org/10.2305/IUCN.UK.2018 2.RLTS.T22682528A132400385.en.
Barbet-Massin M, Jiguet F, Albert CH, Thuiller W. 2012. Selecting pseudo-absences for species distribution models: How, where and how many? Methods in Ecology and Evolution. 3: 327–338. doi:10.1111/j.2041-210X.2011.00172.x.
Berg CC, Corner EJ. 2005. Moraceae: Ficeae. Flora Malesiana – Series 1, Spermatophyta. 17: 1–702.
Bibby C, Jones M, Marsden, S. 2000. Survei Burung. SMKG Mardi Yuana. Bogor
Cohen J. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement. 20(1): 37 – 46. doi:10.1177/001316446002000104.
Condro AD. 2020. Dinamika distribusi spasial primata: Perubahan iklim dan impilkasinya terhadap pengelolaan konservasi [tesis]. Bogor (ID): Institut Pertanian Bogor.
Congalton RG, Green K. 1999. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, Florida (US): CRC Press, Inc
Cutler DR, Edwards Jr TC, K.H. Beard KH, Cutler A, Hess KT, Gibson J, Lawler JJ. 2007. Random forests for classification in ecology. Ecology. 88(11): 2783–2792. doi:10.1890/07-0539.1
Datta A. 1998. Hornbill abundance in unlogged forest, selectively logged forest and a forest plantation in Arunachal Pradesh, India. Oryx 32. 4:285-294.
[Dephut] Departemen Kehutanan. 2005. Pedoman Inventarisasi dan Identifikasi Lahan Kritis Mangrove. Jakarta (ID): Departemen Kehutanan Direktorat Jenderal Rehabilitasi Lahan dan Perhutanan Sosial.
Duan RY, Kong XQ, Huang MY, Fan WY, Wang ZG. 2014. The Predictive Performance and Stability of Six Species Distribution Models. Plos One. PLoS ONE 9(11): e112764. doi:10.1371/journal.pone.0112764
Franklin, J. 2009. Mapping Species Distribution: Spatial Inference and Prediction. New York, United States of America: Cambridge University Press.
Ghozali I. 2009. Aplikasi Analisis Multivarite dengan SPSS, Cetakan Keempat. Semarang (ID) : Badan Penerbit Universitas Diponegoro.
Jarulis. 2019. Karakteristik Marfologi dan Genetik Burung Rangkong (Aves: Bucerotidae) serta penyebarannya di Indonesia [disertasi]. Bogor (ID): Institut Pertanian Bogor.
Johns AD. 1988. The use primary and selectively logged rainforest by Malaysian Hornbills (Bucerotidae) and Implications for their Conservation. Biological Conservation. 40(1): 179 -190.
Kamal S, Agustina E, Azhari. 2018. Populasi rangkong papan (Buceros bicornis) di ekosistem Tahura Pocut Meurah Intan Provinsi Aceh. Jurnal Biologi. 14(1): 10-19.
Kinnaird MF, O’Brien TG. 2005. Fast foods of the forest: the influence of figs on primates and hornbills across Wallace’s Line. In: Tropical Fruit and Frugivores: The Search for Strong Interactions (J.L. Dew & J.P. Boubli, eds), pp. 155–184. Zoological Society of San Diego, San Diego.
Kubangun SH, Haridjaja O, Gandasasmita K. 2016. Model perubahan penutupan/ penggunaan lahan untuk identifikasi lahan kritis di Kabupaten Bogor, Kabupaten Cianjur, dan Kabupaten Sukabumi. Majalah Ilmiah Globe. 18(1): 21–32.
Kumara I. 2006. Karakteristik spasial habitat burung rangkong di Taman Nasional Danau Sentarum [tesis]. Bogor: Sekolah Pascasarjana Institut Pertanian Bogor.
Kutner MH, Nachtsheim CJ, Neter J, Li W. 2005. Applied Linear Statistical Models. 5th Edition. New York(US): McGraw-Hill/Irwin.
Liang H, Guoa Z, Wua J, Chena Z. 2020. GDP spatialization in Ningbo City based on NPP/VIIRS night-time light and auxiliary data using random forest regression. Advanses in Space Research. 481-493.
Liaw A, Wiener M. 2002. Classification and Regression by randomForest. R News. 2: 18–22.
Lobo JM, Jimenez-Valverde A, Real R. 2008. AUC: a misleading measure of the performance of predictive distribution models. Glob. Ecol. Biogeogr. 17: 145 – 151. doi:10.1111/j.1466-8238.2007.00358.x.
Hadiprakarsa Y, Kinnaird MF. 2005. Foraging characteristics of an assemblage of Four Sumatran hornbill species. Bird Conservation International. 14:S53-S62-S53-S62.
Hadiprakarsa Y, Winarni NL. 2007. Fragmentasi hutan di Lampung, Sumatera vs burung rangkong: Mampukah burung rangkong bertahan hidup? Jurnal Indonesian Ornithologists’ Union (IdOU). 5 (1): 94―102.
Hadiprakarsa Y. 2008. Forest patch occupancy by sumatran hornbills in a fragmented landscape of southern sumatra, Indonesia [tesis]. Georgia : The University of Georgiax
Hijmans RJ, Phillips S, Leathwick J, Elith J. 2015. Dismo: Species Distribution Modeling. R Package Version 1.0-12 [internet]. [diakses 2021 Jul 14]. Tersedia pada: http://CRAN.R-project.org/package=dismo.
Hastie T, Tibshirani R, Friedman, J. 2009. The elements of statistical learning: Data mining, inference, and prediction (2nd ed., Vol. 1). New York (NY): Springer series in statistics New York. doi: 10.1007/978-0-387-84858-7.
Hidayat RA, Febriani N, Hanif M, Rahman H. 2020. Modeling of conservation priority the Helmeted Hornbil (Rhinoplax vigil) in Silokek Geopark Area, West Sumatera. doi:10.20944/preprints202009.0676.v1.
Hidayat RZ, Febriani N. 2021. Pemodelan probabilitas sebaran habitat untuk menentukan kawasan prioritas konservasi burung rangkong gading (rhinoplax vigil) di Geopark Silokek, Kabupaten Sijunjung. Konservasi Hayati.1 (1): 35-43.
Kutner MH, Nachtsheim CJ, Neter J, Li W. 2005. Applied Linear Statistical Models. 5th Edition. New York: McGraw-Hill/Irwin.
Liaw A, Wiener M. 2002. Classification and Regression by randomForest. R News. 2: 18–22.
Mackinnon J, Phillips K, Balen BV. 2010. Burung-Burung di Sumatera, Jawa, Bali, dan Kalimantan (Termasuk Sabah, Serawak, dan Brunei Darussalam). Bogor (ID): Burung Indonesia
Mercadier M, Lardy JP. 2019. Credit Spread Approximation and Improvement Using Random Forest Regression. European Journal of Operational Research. 351-365.
Meyer D. 2012. Support Vector Machine, The interface to libsvm in package e1071. Austria: FH Technikum Wien.
Nugraha CA. 2015. Pemodelan Spasial Kesesuaian Habitat Elang Jawa (Nisaetus bartelsi Stresemann, 1924) di Taman Nasional Gunung Halimun Salak [tesis]. Bogor (ID): Institut Pertanian Bogor.
Pramana GTS, Prasetyo LB, Iskandar E. 2023. The habitat suitability modelling of dare monkey (Macaca maura) in Bantimurung Bulusaraung National Park, South Sulawesi. Journal of Natural Resources and Environmental Management. 13(1): 57–67. doi:10.29244/jpsl.13.1.57–67.
Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling. 190(3-4): 231–259. doi:10.1016/j.ecolm odel.2005.03.026.
Pearson RG, Dawson TP. 2003. Predicting the impacts of climate change on the distribution of species: Are bioclimate envelope models useful? Global Ecology and Biogeography. 12: 361-371. doi:10.1046/j.1466-822X.2003.00042.x.
Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT. 2007. Predicting species distributions from small numbers of occurence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography. 34: 102–117.
Pudyatmoko S, Djuwantoko, Sabarno Y. 2007. Evidence of banteng (Bos javanicus) decline in Baluran National Park, Indonesia. Journal of Biological Sciences. 7(6): 854– 859. doi:10.3923/jbs.2007.854.859.
Rahman H. (2020). Spatial Assessment of Landscape Structure Changes an Ecological Connectivity in Pariaman. Journal of Remote Sensing GIS dan Technology. 6(1): 10-22.
Sodik M, Pudyatmoko S, Yuwono PSH, Imron MA. 2019. Okupansi Kukang Jawa (Nycticebus javanicus E. Geoffroy 1812) di Hutan Tropis Dataran Rendah di Kemuning, Bejen, Temanggung, Jawa Tengah. Jurnal Ilmu Lingkungan. 13: 15-27. doi:10.22146/jik.46141.
Strobl C, Boulesteix L, Zeileis A, Hothorn T. 2007. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinf, 8(1):25. doi:10.1186/1471-2105-8-25
Sunaryo S, Setiawan S, Siagian TH. 2015. Mengatasi Masalah Multikolinearitas dan Outlier dengan Pendekatan ROBPCA (Studi Kasus Analisis Regresi Angka Kematian Bayi di Jawa Timur). Jurnal Matematika, Sains, dan Teknologi. 12(1): 1-10.
Supriyadi R, Gata W, Maulidah N, Fauzi A. 2020. Penerapan algoritma random forest untuk menentukan kualitas anggur merah. Jurnal Ilmiah Ekonomi dan Bisnis. 13(2): 67 – 75.
Syechalad, Muhammad N. 2009. Perkebunan dalam Kajian Sosial Ekonomi. Banda Aceh (ID): Yayasan PENA.
Trainor C, Lesmana D, Gatur A. 2000. Importance of forest in the west side of Timor land-First study of biodiversity and socio-economic information in Timor island of Nusa Tenggara Timur. (Rep. No. 13). PKA/Birdlife International/WWF, Bogor.
Authors
SetiawanT., PrasetyoL. B., MulyaniY. A. and Jarulis (2024) “The Habitat Suitability Modelling of Rhinoceros Hornbills (Buceros rhinoceros) in Java Island, Indonesia”, Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management). Bogor, ID, 14(2), p. 253. doi: 10.29244/jpsl.14.2.253.
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