Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia
Abstract. Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020. Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia. Biodivers...
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oai:doaj.org-article:8f5f64dc62ca4278ae5ff420df4338572021-11-22T00:51:08ZPredicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia1412-033X2085-472210.13057/biodiv/d211053https://doaj.org/article/8f5f64dc62ca4278ae5ff420df4338572020-09-01T00:00:00Zhttps://smujo.id/biodiv/article/view/6864https://doaj.org/toc/1412-033Xhttps://doaj.org/toc/2085-4722Abstract. Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020. Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia. Biodiversitas 21: 4866-4877. Selaginella is a genus of non-flowering plant that requires water as a medium for fertilization, as such, it prefers mountainous areas with high level of humidity. Such unique ecosystem of Selaginella is available in some parts of Java Island, Indonesia, especially in highland areas with altitude of more than 1,000 meters above sea level. However, most mountainous areas in Java are likely to be affected by climate change due to global warming, threatening the habitat and sustainability of Selaginella. This study aimed to investigate the impacts of climate change on the geographical distribution of Selaginella opaca Warb. and Selaginella remotifolia Spring. In doing so, we predicted the suitable habitats of both species using Species Distribution Model (SDM) tool of MaxEnt under present climate conditions and future conditions under four climate change scenarios. Species occurrence data were obtained from fieldworks conducted in 2007-2014 across Java Island (283 points: 144 and 139 points for S. opaca and S. remotifolia, respectively) and combined with secondary data from Global Biodiversity Information Facility (GBIF) (52 points: 35 and 17 points for S. opaca and S. remotifolia, respectively), and this dataset was used to model present geographical distribution using environmental and bioclimatic variables. Then, future distribution was predicted under four climate change scenarios: i.e. RCP (Representative Carbon Pathways) 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 in three different time periods (2030, 2050, and 2080). The results of the models showed that the extent of suitable habitats of S. opaca and S. remotifolia will be reduced between 1.8-11.4% due to changes in climatic condition, and in the areas with high level of habitat suitability, including Mount Sumbing, Mount Sindoro and Mount Dieng (Dieng Plateau), the reduction can reach up to 60%. This study adds another context of evidence to understand the potential impacts of climate change on biodiversity, especially on climate-sensitive species, such as Selaginella, in climate-risk regions like mountainous areas of Java Island.AHMAD DWI SETYAWANJATNA SUPRIATNANISYAWATI NISYAWATIILYAS NURSAMSISUTARNO SUTARNOSUGIYARTO SUGIYARTOSUNARTO SUNARTOPRAKASH PRADANSUGENG BUDIHARTAARI PITOYOSAPTA SUHARDONOPRABANG SETYONOMUHAMMAD INDRAWANMBI & UNS Soloarticlejava, mountainous areas, climate change, selaginella ornata, selaginella remotifoliaBiology (General)QH301-705.5ENBiodiversitas, Vol 21, Iss 10 (2020) |
institution |
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DOAJ |
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topic |
java, mountainous areas, climate change, selaginella ornata, selaginella remotifolia Biology (General) QH301-705.5 |
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java, mountainous areas, climate change, selaginella ornata, selaginella remotifolia Biology (General) QH301-705.5 AHMAD DWI SETYAWAN JATNA SUPRIATNA NISYAWATI NISYAWATI ILYAS NURSAMSI SUTARNO SUTARNO SUGIYARTO SUGIYARTO SUNARTO SUNARTO PRAKASH PRADAN SUGENG BUDIHARTA ARI PITOYO SAPTA SUHARDONO PRABANG SETYONO MUHAMMAD INDRAWAN Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
description |
Abstract. Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020. Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia. Biodiversitas 21: 4866-4877. Selaginella is a genus of non-flowering plant that requires water as a medium for fertilization, as such, it prefers mountainous areas with high level of humidity. Such unique ecosystem of Selaginella is available in some parts of Java Island, Indonesia, especially in highland areas with altitude of more than 1,000 meters above sea level. However, most mountainous areas in Java are likely to be affected by climate change due to global warming, threatening the habitat and sustainability of Selaginella. This study aimed to investigate the impacts of climate change on the geographical distribution of Selaginella opaca Warb. and Selaginella remotifolia Spring. In doing so, we predicted the suitable habitats of both species using Species Distribution Model (SDM) tool of MaxEnt under present climate conditions and future conditions under four climate change scenarios. Species occurrence data were obtained from fieldworks conducted in 2007-2014 across Java Island (283 points: 144 and 139 points for S. opaca and S. remotifolia, respectively) and combined with secondary data from Global Biodiversity Information Facility (GBIF) (52 points: 35 and 17 points for S. opaca and S. remotifolia, respectively), and this dataset was used to model present geographical distribution using environmental and bioclimatic variables. Then, future distribution was predicted under four climate change scenarios: i.e. RCP (Representative Carbon Pathways) 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 in three different time periods (2030, 2050, and 2080). The results of the models showed that the extent of suitable habitats of S. opaca and S. remotifolia will be reduced between 1.8-11.4% due to changes in climatic condition, and in the areas with high level of habitat suitability, including Mount Sumbing, Mount Sindoro and Mount Dieng (Dieng Plateau), the reduction can reach up to 60%. This study adds another context of evidence to understand the potential impacts of climate change on biodiversity, especially on climate-sensitive species, such as Selaginella, in climate-risk regions like mountainous areas of Java Island. |
format |
article |
author |
AHMAD DWI SETYAWAN JATNA SUPRIATNA NISYAWATI NISYAWATI ILYAS NURSAMSI SUTARNO SUTARNO SUGIYARTO SUGIYARTO SUNARTO SUNARTO PRAKASH PRADAN SUGENG BUDIHARTA ARI PITOYO SAPTA SUHARDONO PRABANG SETYONO MUHAMMAD INDRAWAN |
author_facet |
AHMAD DWI SETYAWAN JATNA SUPRIATNA NISYAWATI NISYAWATI ILYAS NURSAMSI SUTARNO SUTARNO SUGIYARTO SUGIYARTO SUNARTO SUNARTO PRAKASH PRADAN SUGENG BUDIHARTA ARI PITOYO SAPTA SUHARDONO PRABANG SETYONO MUHAMMAD INDRAWAN |
author_sort |
AHMAD DWI SETYAWAN |
title |
Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
title_short |
Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
title_full |
Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
title_fullStr |
Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
title_full_unstemmed |
Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia |
title_sort |
predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in java, indonesia |
publisher |
MBI & UNS Solo |
publishDate |
2020 |
url |
https://doaj.org/article/8f5f64dc62ca4278ae5ff420df433857 |
work_keys_str_mv |
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