PREDICTING THE IMPACT OF CLIMATE CHANGE ON THE DISTRIBUTION OF Flindersia pimenteliana F. Muell. IN INDONESIAN PAPUA AND PAPUA NEW GUINEA
Downloads
Population of Flindersia pimenteliana (Maple Silkwood) in Indonesian Papua and Papua New Guinea is severely fragmented and experiencing a continuing decline due to habitat destruction and illegal logging. This species is very susceptible to environmental changes and at greater risk of extinction due to its small and fragmented geographic ranges and low abundance. Using maximum entropy (MaxEnt) method, the present study predicted the impact of climate change on the distribution of the species across its native distribution area. Elevation and 19 bioclimatic variables commonly used in species distribution modeling were used as predictors. Â The prediction model of the current potential distribution identified a total area of 156,214 km2 in Indonesian Papua and Papua New Guinea (18% of total land area) as suitable habitat for F. pimenteliana. Elevation and precipitation of the wettest, coldest and warmest quarters contributed most to the model. Based on the average of HadGEM2-ES and MIROC-ESM models, potential distribution projections under RCP8.5 scenario suggested a habitat gain of 16% for 2050 and 8% for 2070 in the species distribution. Whereas under RCP4.5, an average habitat gain of 7% was predicted for both 2050 and 2070. The newly suitable habitats were predicted to be found mainly in Southern and Western Highland of Papua New Guinea. Protection of these areas from habitat destruction and land use change is needed to assist F. pimenteliana find the most suitable climate for its survival.
Anderson RP, Raza A. 2010. The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: Preliminary tests with montane rodents (genus Nephelomys) in Venezuela. J Biogeogr 37:1378–93.
Australian Bureau of Meteorology, CSIRO. 2011. Climate change in the Pacific: Scientific assessment and new research. Volume 2: Country Reports. Available from: http://www.pacificclimatechangescience.org/wp-content/uploads/2013/09/Papua-New-Guinea.pdf
. Retrieved on 16 August 2016.
Baltzer JL, Davies SJ. 2012. Rainfall seasonality and pest pressure as determinants of tropical tree species distributions. Ecol Evol 2(11):2682–94.
Baltzer JL, Davies SJ, Bunyavejchewin S, Noor NSM. 2008. The role of desiccation tolerance in determining tree species distributions along the Malay–Thai Peninsula. Funct Ecol 22:221–31.
Barbet-Massin M, Jiguet F, Albert CH, Thuiller W. 2012. Selecting pseudo-absences for species distribution models: How, where, and how many? Methods Ecol Evol 3:327–38.
Boer R, Faqih A. 2004. Current and future rainfall variability in Indonesia. In: Lasco RD, Boer R, editors. An integrated assessment of climate change impacts, adaptation and vulnerability in watershed areas and communities in Southeast Asia. Report from AIACC Project No. AS21 (Annex C, p.95–126). Washington, DC (US): International START Secretariat.
Boria RA, Olson LE, Goodman SM, Anderson RA. 2014. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol Model 275:73–7.
Brenes-Arguedas T, Coley PD, Kursar TA. 2009. Pests vs. drought as determinants of plant distribution along a tropical rainfall gradient. Ecology 90(7):1751–61.
Brown JL. 2014. SDMtoolbox: A Python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses. Methods Ecol Evol 5(7):694–700.
Chen IC, Hill JK, Ohlemüller R, Roy DB, Thomas CD. 2011. Rapid range shifts of species associated with high levels of climate warming. Science 333:1024–6.
Conn BJ, Damas KQ. 2006. Guide to trees of Papua New Guinea. Available from: http://www.pngplants.org/PNGtrees
. Retrieved on 16 August 2016.
Eddowes PJ. 1998. The IUCN Red List of Threatened Species: Flindersia pimenteliana. Version 2014.3. Available from: www.iucnredlist.org
. Retrieved on 16 April 2016.
Elith J, Graham CH, Anderson RP, Dudik M, Ferrier S, Guisan A, Hijmans RJ, Huettmann F, Leathwick JR, Lehmann A, et al. 2006. Novel methods improve prediction of species distributions from occurrence data. Ecography 29:129–51.
Engelbrecht BMJ, Comita LS, Condit R, Kursar TA, Tyree MT, Turner BL, Shubbell SP. 2007. Drought sensitivity shapes species distribution patterns in tropical forests. Nature 447:80–2.
Franklin J. 2013. Species distribution models in conservation biogeography: Developments and challenges. Divers Distrib 19:1217–23.
Guillera-Arroita G, Lahoz-Monfort JJ, Elith J, Gordon A, Kujala H, Lentini PE, McCarthy MA, Tingley R, Wintle BA. 2015. Is my species distribution model fit for purpose? Matching data and models to applications. Global Ecol Biogeogr 24:276–92.
Guisan A, Tingley R, Baumgartner JB, Naujokaitis-Lewis I, Sutcliffe PR, Tulloch AIT, et al. 2013. Predicting species distributions for conservation decisions. Ecol Lett 16:1424–35.
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–78.
Hijmans RJ. 2012. Cross-validation of species distribution models: Removing spatial sorting bias and calibration with a null model. Ecology 93:679–88.
Hu J, Hu H, Jiang Z. 2010. The impacts of climate change on the wintering distribution of an endangered migratory bird. Oecologia 164:555–65.
IPCC. 2013. Climate change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge (UK): Cambridge University Press. 1535 p.
Liu C, Newell G, White M. 2016. On the selection of thresholds for predicting species occurrence with presence-only data. Ecol Evol 6(1):337–48.
Liu C, White M, Newell G. 2013. Selecting thresholds for the prediction of species occurrence with presence-only data. J Biogeogr 40(4):778–89.
Merow C, Smith MJ, Silander JA. 2013. A practical guide to MaxEnt for modeling species distributions: What it does, and why inputs and settings matter. Ecography 36:1058–69.
Nix HA. 1986. A biogeographic analysis of Australian elapid snakes. In: Longmore R, editor. Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series No. 7. Canberra (AU): Australian Government Publishing Service. p. 4–15.
Pearson RG. 2007. Species distribution modeling for conservation educators and practitioners. Synthesis. New York (US): American Museum of Natural History. Available from: http://ncep.amnh.org
. Retrieved on 11 November 2015.
Peterson AT, Soberón J, Pearson RG, Anderson RP, Martínez-Meyer E, Nakamura M, Araújo M. 2011. Ecological niches and geographic distributions. New Jersey (US): Princeton University Press. 328 p.
Phillips SJ, Anderson RP, Schapire RE. 2006. Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–59.
Purnawati R, Wahyudi I, Priadi T. 2012. Anatomical properties of Flindersia pimenteliana from Wondama Bay, West Papua. Jurnal Ilmu dan Teknologi Kayu Tropis 10(2):122–9.
Purnawati R. 2013. Basic and processing properties of maniani (Flindersia v. Muell) wood from Papua. Master Thesis. Bogor (ID): Bogor Agricultural University. 65 p.
Radosavljevic A, Anderson RP. 2014. Making better Maxent models of species distributions: Complexity, overfitting and evaluation. J Biogeogr 41(4):629–43.
Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, et al. 2011. RCP 8.5 – A scenario of comparatively high greenhouse gas emissions. Clim Change 109:33–57.
Roberts DR, Hamann A. 2012. Predicting potential climate change impacts with bioclimate envelope models: A palaeoecological perspective. Glob Ecol Biogeogr 21(2):121–33.
Schuur EAG. 2003. Productivity and global climate revisited: The sensitivity of tropical forest growth to precipitation. Ecology 84(5):1165–70.
Soberón J. 2007. Grinnellian and Eltonian niches and geographic distributions of species. Ecol Lett 10:1115–23.
Toledo M, Pena-Claros M, Bongers F, Alarcon A, Balcazar J, et al. 2012. Distribution patterns of tropical woody species in response to climatic and edaphic gradients. J Ecol 100:253–63.
Trisurat Y, Shrestha RP, Kjelgren R. 2011. Plant species vulnerability to climate change in Peninsular Thailand. Appl Geogr 31:1106–14.
Van Der Wal J, Shoo LP, Graham C, Williams SE. 2009. Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know? Ecol Model 220(4):589–94.
Veloz SD. 2009. Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models. J Biogeogr 36:2290–9.
Walck JL, Hidayati SN, Dixon KW, Thompson K, Poschlod P. 2011. Climate change and plant regeneration from seed. Glob Change Biol 17:2145–61.
Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A. 2008. Effects of sample size on the performance of species distribution models. Divers Distrib 14:763–73.
Copyright (c) 2017 BIOTROPIA - The Southeast Asian Journal of Tropical Biology

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree with the following terms:
- Authors retain copyright and grant the journal right of first publication, with the work 1 year after publication simultaneously licensed under a Creative Commons attribution-noncommerical-noderivates 4.0 International License that allows others to share, copy and redistribute the work in any medium or format, but only where the use is for non-commercial purposes and an acknowledgement of the work's authorship and initial publication in this journal is mentioned.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).




