Contributing Environmental Factors of Habitat Suitability for the Great Argus (Argusianus argus) in Bukit Barisan Selatan National Park, Indonesia
Article Sidebar
-
habitat suitability, MaxEnt, phasianidae, prediction
Abstract
The great argus (Argusianus argus), a key outstanding universal value (OUV) species in Bukit Barisan Selatan National Park (BBSNP) within the tropical rainforest heritage of Sumatra (TRHS), is listed as vulnerable by the IUCN red list due to extensive deforestation and habitat fragmentation. Yet, its habitat preferences and spatial distribution remain poorly understood. This study aimed to model the potential distribution of the great argus and identify key environmental factors influencing its occurrence within the Way Canguk Research Station (WCRS), BBSNP. We employed the Maximum Entropy (MaxEnt) algorithm using data from field surveys and camera traps combined with environmental variables including elevation, slope, distance to rivers, normalized difference moisture index (NDMI), temperature, rainfall, distance to roads and settlements, NDVI, and land cover. The model exhibited high predictive performance (AUC = 0.846). Distance to roads, rainfall intensity, and the presence of primary forest emerged as the most influential factors. The species showed a preference for primary forests located far from human disturbances and in areas with lower rainfall levels. These findings confirm WCRS as a suitable habitat for the great argus and underscore the urgency of preventing deforestation, restoring degraded lands, and mitigating road impacts to preserve BBSNP’s ecological integrity and sustain TRHS’s world heritage status.
Full text article
References
Alam, K. F., & Ahamed, T. (2023). Climate-adaptive potential crops selection in vulnerable agricultural lands adjacent to the Jamuna River Basin of Bangladesh using remote sensing and a fuzzy expert system. Remote Sensing, 15(8), Article 2201. https://doi.org/10.3390/rs15082201
Ascensão, F., D’Amico, M., Revilla, E., & Pereira, H. M. (2022). Road encroachment mediates species occupancy, trait filtering and dissimilarity of passerine communities. Biological Conservation, 270, Article 109590. https://doi.org/10.1016/j.biocon.2022.109590
Azahar, M. A., Azman, M. S., Ahmad Ruzman, N. H., Appanan, M., Zam Beri, A. Z., Baharudin, M. S., Rosli, R., Samihon, S. A., Gara, S., Samihon, S., Eliah, A. E., & Kamaruzzaman, M. F. (2023). Observations on vertebrates at Padang Chong Forest Reserve, Perak. BIO Web of Conferences, 73, Article 01006. https://doi.org/10.1051/bioconf/20237301006
Balata, D., Gama, I., Domingos, T., & Proença, V. (2022). Using satellite NDVI time-series to monitor grazing effects on vegetation productivity and phenology in heterogeneous Mediterranean forests. Remote Sensing, 14(10), Article 2322. https://doi.org/10.3390/rs14102322
BirdLife International. (2020). Argusianus argus. The IUCN red list of threatened species 2020: e.T22725006A183255774. https://doi.org/10.2305/IUCN.UK.2020-3.RLTS.T22725006A183255774.en
Brocardo, C. R., Rosa, D. C. P., Castro, A. B., Rosa, C., Torralvo, K., Pequeno, P., Magnusson, W. E., & Fadini, R. F. (2023). Responses of ground-dwelling birds and mammals to local environmental variables and human pressure in an Amazonian protected area. European Journal of Wildlife Research, 69(3), Article 48. https://doi.org/10.1007/s10344-023-01677-z
Campos, J. C., Garcia, N., Alírio, J., Arenas-Castro, S., Teodoro, A. C., & Sillero, N. (2023). Ecological niche models using MaxEnt in Google Earth Engine: Evaluation, guidelines and recommendations. Ecological Informatics, 76, Article 102147. https://doi.org/10.1016/j.ecoinf.2023.102147
Chan, J. Y., Mun, S., Leow, H., Bea, K. T., Cheng, W. K., Phoong, S. W., Hong, Z., & Chen, Y. (2022). Mitigating the multicollinearity problem and its machine learning approach : A review. Mathematics, 10(8), Article 1823. https://doi.org/10.3390/math10081283
Cheng, J. H., Chen, Z. G., & Yi, S. J. (2022). Wavelength selection algorithm based on minimum correlation coefficient for multivariate calibration. Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis, 42(3), 719–725. https://doi.org/10.3964/j.issn.1000-0593(2022)03-0719-07
Clink, D. J., Groves, T., Ahmad, A. H., & Klinck, H. (2021). Not by the light of the moon: Investigating circadian rhythms and environmental predictors of calling in Bornean great argus. PLoS ONE, 16(2), Article e0246564. https://doi.org/10.1371/journal.pone.0246564
Davison, G. W. H. (1981a). Sexual selection and the mating system of Argusianus argus (Aves: Phasianidae). Biological Journal of the Linnean Society, 15(2), 91–104. https://doi.org/10.1111/j.1095-8312.1981.tb00751.x
Davison, G. W. H. (1981b). Diet and dispersion of the great argus Argusianus argus. Ibis, 123(4), 485–494. https://doi.org/10.1111/j.1474-919X.1981.tb04052.x
de Albuquerque, F. S., Bateman, H. L., Boehme, C., Allen, D. C., & Cayuela, L. (2021). Variation in temperature, precipitation, and vegetation greenness drive changes in seasonal variation of avian diversity in an urban desert landscape. Land, 10(5), Article 0480. https://doi.org/10.3390/land10050480
Debataraja, I. B., Pradana, D. H., & Winarni, N. L. (2021). The impact of landuse and the relationship between NDVI on the bird species richness in Sukmajaya District, Depok. IOP Conference Series: Earth and Environmental Science, 846(1), Article 012004. https://doi.org/10.1088/1755-1315/846/1/012004
Etaga, H. O., Ndubisi, R. C., & Oluebube, N. L. (2021). Effect of multicollinearity on variable selection in multiple regression. Science Journal of Applied Mathematics and Statistics, 9(6), 141–153. https://doi.org/10.11648/j.sjams.20210906.12
Gregory, A., Spence, E., Beier, P., & Garding, E. (2021). Toward best management practices for ecological corridors. Land, 10(2), Article 140. https://doi.org/10.3390/land10020140
Guan, X., Rao, X., Song, G., & Wang, D. (2022). The evolution of courtship displays in Galliformes. Avian Research, 13, Article 100008. https://doi.org/10.1016/j.avrs.2022.100008
Hamirul, S., Izereen, M., Azmin, H., Izzati, A., Ainur, B., Nabihah, M., Izyan, S., Syafiq, N., Izzat, N., Syafiq, S., Aainaa, A., Norashikin, F., Hizami, H., Azahar, A., Firdaus, K., Amal, N., Ai Yin, S., Lukman, I., Yusoff, S., & Kamarul, H. (2021). Camera trap survey of wildlife in State Land Forest, Merapoh, Pahang, Malaysia. Malaysian Forester, 84(2), 283–295.
Hasan, S. H., AL-Hameedawi, A. N. M., & Ismael, H. S. (2022). Supervised classification model using Google Earth Engine development environment for Wasit Governorate. IOP Conference Series: Earth and Environmental Science, 961(1), Article 012051. https://doi.org/10.1088/1755-1315/961/1/012051
Hilwan, I., & Anggoro, P. (2023). Studi populasi dan distribusi palahlar (Dipterocarpus hasseltii Blume) di Resort Gunung Salak I, Taman Nasional Gunung Halimun Salak. Jurnal Silvikultur Tropika, 14(3), 229–235. https://doi.org/10.29244/j-siltrop.14.03.229-235
Jambari, A., Hosaka, T., Nakabayashi, M., Yahya, M. S., & Azhar, B. (2023). Conservation planning in national parks may benefit from site occupancy and detection estimates of native animal species. Journal for Nature Conservation, 75, Article 126463. https://doi.org/10.1016/j.jnc.2023.126463
Javidan, N., Kavian, A., Pourghasemi, H. R., Conoscenti, C., Jafarian, Z., & Rodrigo-Comino, J. (2021). Evaluation of multi-hazard map produced using MaxEnt machine learning technique. Scientific Reports, 11(1), Article 6496. https://doi.org/10.1038/s41598-021-85862-7
Jean-Pierre, A., Loranger-Merciris, G., & Cézilly, F. (2022). Spatial occupancy, local abundance and activity rhythm of three ground dwelling Columbid species in the forests of Guadeloupe in relation to environmental factors. Diversity, 14(6), Article 0480. https://doi.org/10.3390/d14060480
Lah, N. Z. A., Yusop, Z., Hashim, M., Salim, J. M., & Numata, S. (2021). Predicting the habitat suitability of Melaleuca cajuputi based on the maxent species distribution model. Forests, 12(11), Article 1449. https://doi.org/10.3390/f12111449
Laneng, L. A., Nakamura, F., Tachiki, Y., & Vairappan, C. S. (2021). Camera-trapping assessment of terrestrial mammals and birds in rehabilitated forest in INIKEA Project Area, Sabah, Malaysian Borneo. Landscape and Ecological Engineering, 17(2), 135–146. https://doi.org/10.1007/s11355-020-00442-7
Mafuwe, K., Broadley, S., & Moyo, S. (2022). Use of maximum entropy (Maxent) niche modelling to predict the occurrence of threatened freshwater species in a biodiversity hotspot of Zimbabwe. African Journal of Ecology, 60(3), 557–565. https://doi.org/10.1111/aje.12928
Mijwil, M. M., & Aljanabi, M. (2024). A comparative analysis of machine learning algorithms for classification of diabetes utilizing confusion matrix analysis. Baghdad Science Journal, 21(5), Article 24. https://doi.org/10.21123/BSJ.2023.9010
Mili, S. A., Islam, M. S., Al Momen Sabuj, A., Haque, Z. F., Pondit, A., Hossain, M. G., Hassan, J., & Saha, S. (2022). A cross-sectional seroepidemiological study on infectious bursal disease in backyard chickens in the Mymensingh District of Bangladesh. Veterinary Medicine International, 2022, Article 9076755. https://doi.org/10.1155/2022/9076755
Mishra, A., Nair, N. S., Harichandrakumar, K., Binu, V., & Satheesh, S. (2022). Application of principal component analysis in dealing with multicollinearity in modelling clinical data. Journal of Clinical and Diagnostic Research, 16(7), YC15–YC19. https://doi.org/10.7860/jcdr/2022/55379.16629
Morante-Filho, J. C., Benchimol, M., & Faria, D. (2021). Landscape composition is the strongest determinant of bird occupancy patterns in tropical forest patches. Landscape Ecology, 36(1), 105–117. https://doi.org/10.1007/s10980-020-01121-6
Naiheli, F. R., Seran, W., Pramatana, F., & Kaho, L. M. R. (2022). Struktur dan komposisi serta status regenerasi mamar Desa Beaneno, Kecamatan Sasitamean, Kabupaten Malaka. Jurnal Kehutanan Papuasia, 8(2), 342–355. https://doi.org/10.46703/jurnalpapuasia.vol8.iss2.368
Navarro, A. B., Magioli, M., Bogoni, J. A., Moreira, M. Z., Silveira, L. F., Alexandrino, E. R., da Luz, D. T. A., Pizo, M. A., Silva, W. R., de Oliveira, V. C., Donatelli, R. J., Christianini, A. V., Piratelli, A. J., & Ferraz, K. M. P. M. B. (2021). Human-modified landscapes narrow the isotopic niche of neotropical birds. Oecologia, 196(1), 171–184. https://doi.org/10.1007/s00442-021-04908-9
Nijman, V. (1998). Habitat preference of great argus pheasant Argusianus argus in Kayan Mentarang National Park, East Kalimantan, Indonesia. Journal fur Ornithologie, 139(3), 313–323. https://doi.org/10.1007/BF01653342
Ong-In, T. I. W. A., & Savini, T. (2021). Hydropower reservoir reduces great argus Argusianus argus density in proximity to its shore. Bird Conservation International, 33, Article e3. https://doi.org/10.1017/S0959270921000368
Palencia, P., Rowcliffe, J. M., Vicente, J., & Acevedo, P. (2021). Assessing the camera trap methodologies used to estimate density of unmarked populations. Journal of Applied Ecology, 58(8), 1583–1592. https://doi.org/10.1111/1365-2664.13913
Pérez‐Granados, C., & Traba, J. (2021). Estimating bird density using passive acoustic monitoring: A review of methods and suggestions for further research. Ibis, 163(3), 765–783. https://doi.org/10.1111/ibi.12944
Phillips, S. J., & Dudík, M. (2008). Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography, 31(2), 161–175. https://doi.org/10.1111/j.0906-7590.2008.5203.x
Prastio, B., Santoso, A., Roekhan, Maulidina, A., Numertayasa, I. W., & Suardana, I. P. O. (2023). An ecolinguistic study: The representation of forest conservation practices in the discourse of Anak Dalam Jambi tribe, Indonesia. Cogent Arts and Humanities, 10(1), Article 2262788. https://doi.org/10.1080/23311983.2023.2262788
Rafi, M., Novarino, W., Rizaldi, & Ardiyanto, A. (2017). Aktivitaas kuau raja (Argusianus argus Linnaeus, 1766) pada mating ring di hutan konservasi Kalaweit Supayang, Solok, Sumatera Barat. Metamorfosa: Journal of Biological Sciences, 4(1), 58–64. https://doi.org/10.24843/metamorfosa.2017.v04.i01.p10
Robinson, C. L. K., Proudfoot, B., Rooper, C. N., & Bertram, D. F. (2021). Comparison of spatial distribution models to predict subtidal burying habitat of the forage fish Ammodytes personatus in the Strait of Georgia, British Columbia, Canada. Aquatic Conservation: Marine and Freshwater Ecosystems, 31(10), 2856–2869. https://doi.org/10.1002/aqc.3593
Savini, T., Namkhan, M., & Sukumal, N. (2021). Conservation status of Southeast Asian natural habitat estimated using Galliformes spatio-temporal range decline. Global Ecology and Conservation, 29, Article e01723. https://doi.org/10.1016/j.gecco.2021.e01723
Setyawati, T., Nando, S., Marthy, W., Andayani, N., Sheherazade, & Linkie, M. (2021). Planning to remove UNESCO World Heritage Sites in Sumatra from being ‘In Danger.’ Animal Conservation, 24(2), 149–152. https://doi.org/10.1111/acv.12626
Simamora, T. I., Purbowo, S. D., & Laumonier, Y. (2021). Looking for indicator bird species in the context of forest fragmentation and isolation in West Kalimantan, Indonesia. Global Ecology and Conservation, 27, Article e01610. https://doi.org/10.1016/j.gecco.2021.e01610
Slater, H. D., Gillingham, P. K., Pratt, V., Eaton, B., Fletcher, S., Abdullah, A., Supriadi, & Korstjens, A. H. (2024). Living on the edge: forest edge effects on microclimate and terrestrial mammal activity in disturbed lowland forest in Sumatra, Indonesia. Oryx, 58(2), 228–239. https://doi.org/10.1017/S0030605323000212
Stark, G., Ma, L., Zeng, Z. G., Du, W. G., & Levy, O. (2023). Cool shade and not-so-cool shade: How habitat loss may accelerate thermal stress under current and future climate. Global Change Biology, 29(22), 6201–6216.. https://doi.org/10.1111/gcb.16802
Taloor, A. K., Manhas, D. S., & Kothyari, G. C. (2021). Retrieval of land surface temperature, normalized difference moisture index, normalized difference water index of the Ravi basin using Landsat data. Applied Computing and Geosciences, 9, Article 100051. https://doi.org/10.1016/j.acags.2020.100051
Trisnawati, J., Muharar, S., & Sugiarti, E. (2023). The hudoq mask works potential as a source of learning and moral based local wisdom of Dayak Bahau Busang tribe. The International Journal of Politics and Sociology Research, 10(4), 176–193. https://doi.org/10.35335/ijopsor.v10i4.88
United Nations Educational, Scientific and Cultural Organization. (2004, Januari 9). Tropical rainforest heritage of Sumatra. Retrieved from https://whc.unesco.org/en/list/1167/
Valavi, R., Guillera-Arroita, G., Lahoz-Monfort, J. J., & Elith, J. (2022). Predictive performance of presence-only species distribution models: a benchmark study with reproducible code. Ecological Monographs, 92(1), Article e01486. https://doi.org/10.1002/ecm.1486
Valley, P., Faisão, D., & Palas, V. (2022). Population and risk assessment of sympatric pheasant species. Brazilian Journal of Biology, 84, Article e259582. https://doi.org/10.1590/1519-6984.259582
Villaseñor, N. R., Escobar, M. A. H., & Hernández, H. J. (2021). Can aggregated patterns of urban woody vegetation cover promote greater species diversity, richness and abundance of native birds? Urban Forestry and Urban Greening, 61, Article 127102. https://doi.org/10.1016/j.ufug.2021.127102
Wang, L., & Jackson, D. A. (2023). Effects of sample size, data quality, and species response in environmental space on modeling species distributions. Landscape Ecology, 38(12), 4009–4031. https://doi.org/10.1007/s10980-023-01771-2
Wang, Z., Ma, Q., Liang, S., Liu, Y. A., Liu, L., Huang, C., Chen, K., & Hou, W. (2023). Study on the distribution and habitat suitability of seagrass in the Northern Chinese Seas. Frontiers in Marine Science, 10, Article 1297137. https://doi.org/10.3389/fmars.2023.1297137
Winarni, N. L., Nurcahyo, A., Hadiprakarsa, Y., & Iqbal, M. (2004, January). Effects of forest patch size on Galliformes in Southern Sumatra, Indonesia [Conference paper]. International Galliformes Symposium, Fordingbridge, United Kingdom.
Winarni, N. L., O’Brien, T. G., Carroll, J. P., & Kinnaird, M. F. (2009). Movements, distribution, and abundance of great argus pheasants (Argusianus argus) in a sumatran rainforest. Auk, 126(2), 341–350. https://doi.org/10.1525/auk.2009.07162
Zhao, Y., Liao, J., Bao, X., & Ma, M. (2021). Soil seed bank dynamics are regulated by bird diversity and soil moisture during alpine wetland degradation. Biological Conservation, 263, Article 109360. https://doi.org/10.1016/j.biocon.2021.109360
Authors
Copyright (c) 2026 Jurnal Manajemen Hutan Tropika
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Manajemen Hutan Tropika is an open access journal which means that all contents is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author. This is in accordance with the Budapest Open Access Initiative (BOAI) definition of open access.Article Details
How to Cite
