Predicting the effects of future climate change on the distribution of the genus Selaginella in Java, Indonesia
Article Sidebar
Abstract Views: 22
File Views: 11
Main Article Content
Abstract
Abstract. Setyawan AD, Sutarno, Sugiyarto, Sunarto, Nugroho GD, Supriatna J, Sulton MN. 2026. Predicting the effects of future climate change on the distribution of the genus Selaginella in Java, Indonesia. Asian J For 10 (1): r100134. https://doi.org/10.13057/asianjfor/r100134. Ongoing climate change poses significant threats to ecosystems and species by altering environmental conditions beyond historical norms. Climatic factors strongly influence the distribution of plant species. Selaginella is a fern ally that relies on water for fertilization, making it potentially sensitive to climatic changes. This study assessed the current and future climatic suitability of Selaginella using the Maximum Entropy (MaxEnt) model based on 1,962 occurrence records in Java, Indonesia, and selected bioclimatic, topographic, edaphic, and ultraviolet radiation variables. Model performance was excellent, with a training AUC of 0.934 ± 0.006 and a test AUC of 0.921 ± 0.011. The most influential predictors were precipitation of the driest month (31.6%), elevation (27.6%), and mean temperature of the warmest quarter (12.7%), together accounting for 71.9% of total model contribution. Current climatically suitable habitat covered approximately 63,865 km², concentrated primarily in humid montane regions of West, Central, and East Java. Future projections were generated for three time periods (2030, 2050, and 2080) under four climate scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Stable habitats remained dominant across all scenarios, while centroid analyses revealed a general eastward and northeastern shift of suitable habitat. These results suggest that climate change is likely to drive geographic redistribution rather than widespread collapse of the collective climatic niche of Selaginella in Java. The study highlights the importance of precipitation and elevation in determining habitat suitability and provides a basis for anticipating future conservation challenges associated with climate-driven shifts in species distributions.
Article Details
Issue
Section
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
How to Cite
References
Agnihotri P, Tariq H, Shirke PA, Sidhu OP, Singh H, Dixit V, Khuroo AA, Amla DV, Nautiyal CS. 2017. Climate change-driven shifts in elevation and ecophysiological traits of Himalayan plants during the past century. Curr Sci 112 (3): 595-601. https://doi.org/10.18520/cs/v112/i03/595-601.
Alston AHG. 1935a. The Philippine species of Selaginella. Philipp J Sci 58: 359-382.
Alston AHG. 1935b. The Selaginellae of the Malay Islands I. Java and the Lesser Sunda Islands. Bull Jard Bot Buitenzorg III 13: 432-442.
Alston AHG. 1937. The Selaginellae of the Malay Islands II. Sumatra. Bull Jard Bot Buitenzorg III 14: 175-186.
Alston AHG. 1940. The Selaginellae of the Malay Islands III. Celebes and the Moluccas. Bull Jard Bot Buitenzorg III 16: 343-350.
Avia LQ. 2019. Change in rainfall per decade over Java Island, Indonesia. IOP Conf Ser Earth Environ Sci 374 (1): 012037. https://doi.org/10.1088/1755-1315/374/1/012037.
Beckmann M, Václavík T, Manceur AM, Šprtová L, von Wehrden H, Welk E, Cord AF. 2014. glUV: A global UV-B radiation dataset for macroecological studies, Methods Ecol Evol 5 (4): 372-383. https://doi.org/10.1111/2041-210X.12168.
Brown JL, Bennett JR, French CM. 2017. SDMtoolbox 2.0: The next generation Python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses. PeerJ 5: e4095. https://doi.org/10.7717/peerj.4095.
Brown JL. 2014. SDM toolbox: A Python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses. Methods Ecol Evol 5 (7): 694-700. https://doi.org/10.1111/2041-210X.12200.
Campany CE, Martin L, Watkins JE. 2019. Convergence of ecophysiological traits drives floristic composition of early lineage vascular plants on a tropical forest floor. Ann Bot 123 (5): 793-803. https://doi.org/10.1093/aob/mcy210.
Chen B, Zhang X, Tao J, Wu J, Wang J, Shi P, Zhang Y, Yu C. 2014. The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau. Agric For Meteorol 189-190: 11-18. https://doi.org/10.1016/j.agrformet.2014.01.002.
Cornelissen JHC, Lang SI, Soudzilovskaia NA, During HJ. 2007. Comparative Cryptogam Ecology: A Review of Bryophyte and Lichen Traits that Drive Biogeochemistry. Ann Bot 99 (5): 987-1001. https://doi.org/10.1093/aob/mcm030.
Eickmeier W. 1986. The correlation between high-temperature and desiccation tolerances in a poikilohydric desert plant. Can J Bot 64 (3): 611-617. https://doi.org/10.1139/b86-078.
Evans P, Brown CD. 2017. The boreal-temperate forest ecotone response to climate change. Env Rev 25 (4): 423-431. https://doi.org/10.1139/er-2017-0009.
Fick SE, Hijmans RJ. 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Intl J Clim 37 (12): 4302-4315. https://doi.org/10.1002/joc.5086.
GBIF Secretariat. 2026. Global Biodiversity Information Facility (GBIF). Copenhagen, Denmark. Available from: https://www.gbif.org/ [Accessed 1 June 2026].
Hengl T, Mendes de Jesus J, Heuvelink GB et al. 2017. SoilGrids250m: Global gridded soil information based on machine learning. PLoS one 12 (2): e0169748. https://doi.org/10.1371/journal.pone.0169748.
iNaturalist. 2026. iNaturalist Research-grade Biodiversity Observations. California Academy of Sciences and National Geographic Society. Available from: https://www.inaturalist.org/ [Accessed 1 June 2026].
IPCC. 2014. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds.). Climate change 2014: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom.
Jagels R. 1970. Photosynthetic apparatus in Selaginella. I. Morphology and photosynthesis under different light and temperature regimes. Can J Bot 48 (1): 1843-1852. https://doi.org/10.1139/b70-270.
Masson-Delmotte V, Zhai P, Pörtner HO et al. 2018. Global warming of 1.5 C. [An IPCC Special Report]. IPCC, Geneva.
Mohan S, Bhaskaran PK. 2019. Evaluation of CMIP5 climate model projections for surface wind speed over the Indian Ocean region. Clim Dyn 53: 5415–5435. https://doi.org/10.1007/s00382-019-04874-2.
Navarro-Racines C, Tarapues J, Thornton P, Jarvis A, Ramírez-Villegas J. 2020. High-resolution and bias-corrected CMIP5 projections for climate change impact assessments. Sci Data 7: 7 https://doi.org/10.1038/s41597-019-0343-8.
Oliver TH, Morecroft MD. 2014. Interactions between climate change and land use change on biodiversity: Attribution problems, risks, and opportunities. Wiley Interdisciplinary Rev: Clim Change 5 (3): 317-335. https://doi.org/10.1002/wcc.271.
Padalia H, Srivastava V, Kushwaha SPS. 2014. Modeling the potential invasion range of the alien invasive species, Hyptis suaveolens (L.) Poit in India: Comparison of MaxEnt and GARP. Ecol Inf 22: 36-43. https://doi.org/10.1016/j.ecoinf.2014.04.002.
Phillips DJ, 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.2007.0906-7590.05203.x.
Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecol Model 190 (3-4): 231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026.
Rahman MS, Toiba H, Huang WC. 2021. The impact of climate change adaptation strategies on income and food security: Empirical evidence from small-scale fishers in Indonesia. Sustainability 13 (14): 7905. https://doi.org/10.3390/su13147905.
Royal Botanic Gardens Kew. 2026. Plants of the World Online (POWO). Royal Botanic Gardens, Kew. Available from: https://powo.science.kew.org/ [Accessed 1 June 2026].
Ruszala EM, Beerling DJ, Franks PJ, Chater C, Casson SA, Gray JE, Hetherington AM. 2011. Land plants acquired active stomatal control early in their evolutionary history. Curr Biol 21 (12): 1030-1035. https://doi.org/10.1016/j.cub.2011.04.044.
Schmidt AR, Regalado L, Weststrand S, Korall P, Sadowski EM, Schneider H, Jansen E, Bechteler J, Krings M, Müller P, Wang B, Wang X, Rikkinen J, Seyfullah LJ. 2020. Selaginella was hyperdiverse already in the Cretaceous. New Phytol 228 (4): 1176-1182. https://doi.org/10.1111/nph.16600.
Sekaranom AB. 2023. The characterization of warm temperatures in the central part of Java during the monsoon transition in April 2019. Indones J Geogr 55 (1): 120-128. https://doi.org/10.22146/ijg.75194.
Setyawan AD, Darusman LK. 2008. Review: biflavonoid compounds of Selaginella Pal. Beauv. and its benefit. Biodiversitas 9 (1): 64-81. https://doi.org/10.13057/biodiv/d090114.
Setyawan AD, Sugiyarto S, Susilowati A, Widodo W. 2015c. Diversity and distribution of Selaginella in the Province of Yogyakarta Special Region. Pros Sem Nas Masy Biodiv Indon 1: 987-992. https://doi.org/10.13057/psnmbi/m010505.
Setyawan AD, Sugiyarto S, Widiastuti A. 2015b. Species diversity of Selaginella in the Dieng Plateau, Central Java. Pros Sem Nas Masy Biodiv Indon 1: 980-986. https://doi.org/10.13057/psnmbi/m010504.
Setyawan AD, Supriatna J, Darnaedi D, Rokhmatuloh R, Sutarno S, Sugiyarto S. 2016. Diversity of Selaginella across the altitudinal gradient of the tropical region. Biodiversitas 17 (1): 384-400. https://doi.org/10.13057/biodiv/d170152.
Setyawan AD, Supriatna J, Darnaedi D, Rokhmatuloh, Sutarno, Sugiyarto, Nursamsi I, Komala WR, Pradan P. 2017. Impact of climate change on potential distribution of xero-epiphytic Selaginellas (Selaginella involvens and S. repanda) in Southeast Asia. Biodiversitas 18 (4): 1680-1695. https://doi.org/10.13057/biodiv/d180449.
Setyawan AD, Supriatna J, Nisyawati N, Nursamsi I, Sutarno S, Sugiyarto S, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2021. Projecting the expansion range of Selaginella zollingeriana in the Indonesian archipelago under future climate conditions. Biodiversitas 22 (4): 2088-2103. https://doi.org/10.13057/biodiv/d220458.
Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020b. Anticipated climate changes reveal shifting in habitat suitability of high-altitude Selaginellas in Java, Indonesia. Biodiversitas 21 (11): 5482-5497. https://doi.org/10.13057/biodiv/d211157.
Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020a. Predicting potential impacts of climate change on the geographical distribution of mountainous Selaginellas in Java, Indonesia. Biodiversitas 21:4866-4877. https://doi.org/10.13057/biodiv/d211053.
Setyawan AD, Supriatna J, Nisyawati, Sutarno, Sugiyarto, Nursamsi I. 2018. Predicting impacts of future climate change on the distribution of the widespread Selaginellas (Selaginella ciliaris and S. plana) in Southeast Asia. Biodiversitas 19 (5): 1960-1977. https://doi.org/10.13057/biodiv/d190548.
Setyawan AD, Sutarno S, Sugiyarto S. 2013. Species diversity of Selaginella in Mount Lawu, Java, Indonesia. Biodiversitas 14 (1): 1-9. https://doi.org/10.13057/biodiv/d140101.
Setyawan AD, Sutarno, Sugiyarto, Sunarto, Nursamsi I, Budiharta S, Supriatna J, Pradhan P. 2025. Climate-induced habitat contraction and elevational redistribution of Selaginella willdenowii and S. intermedia in Southeast Asia. Asian J For 9: 440-455. https://doi.org/10.13057/asianjfor/r090224
Setyawan AD. 2014. A new record of naturalized Selaginella uncinata (Desv.) Spring (Selaginellaceae) from Java, Indonesia. Biodiversitas 15 (2): 261-268. https://doi.org/10.13057/biodiv/d150221.
Setyawan AD. 2015a. Diversity of Selaginella in the Province of Banten, Western Java. Pros Sem Nas Masy Biodiv Indon 1 (8): 1810-1815. https://doi.org/10.13057/psnmbi/m010810.
Tagawa M, Iwatsuki K. 1979. Selaginellaceae. In: Smitinand T, Larsen K (eds.). Flora of Thailand. Vol. 3. The Forest Herbarium, Bangkok.
Teutschbein C, Seibert J. 2013. Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? Hydrol Earth Syst Sci 17 (12): 5061-5077. https://doi.org/10.5194/hess-17-5061-2013.
Tsai JL, Shieh WC. 1994. Selaginellaceae. In: Editorial Committee of the Flora of Taiwan (eds). Flora of Taiwan. 2nd ed. Vol. 1. Editorial Committee of the Flora of Taiwan, Taipei.
Weststrand S, Korall P. 2016. A subgeneric classification of Selaginella (Selaginellaceae). Am J Bot 103 (12): 2160-2169. https://doi.org/10.3732/ajb.1600288.
Wong KM. 1982. Critical observations on Peninsular Malaysian Selaginella. Gard Bull Singap 35: 107-135.
Wong KM. 2010. Selaginellaceae. In: Kiew R, Chung RCK, Saw LG, Soepadmo E (eds.). Flora of Peninsular Malaysia Series I: Ferns and Lycophytes. Vol. 1. Forest Research Institute Malaysia, Kepong.
Yoon S, Lee WH. 2021. Methodological analysis of bioclimatic variable selection in species distribution modeling with application to agricultural pests (Metcalfa pruinosa and Spodoptera litura). Comput Electron Agric 190: 106430. https://doi.org/10.1016/j.compag.2021.106430.
Zhang H, Moise A, Liang P, Hanson L. 2013a. The response of summer monsoon onset/retreat in Sumatra-Java and the tropical Australia region to global warming in CMIP3 models. Clim Dyn 40: 377-399. https://doi.org/10.1007/s00382-012-1389-x.
Zhang XC, Nooteboom HP, Kato M. 2013b. Selaginellaceae. In: Wu ZY, Raven PH, Hong DY (eds). Flora of China. Vol. 2-3. Science Press, Beijing & Missouri Botanical Garden Press, St. Louis.
Zhou XM, Zhang LB. 2015. A classification of Selaginella (Selaginellaceae) based on molecular (chloroplast and nuclear), macromorphological, and spore features. Taxon 64 (6): 1117-1140. https://doi.org/10.12705/646.2.