Einzeltreffer — DigiBib

It is vital to understand the distribution area of a threatened plant species for its better conservation and management planning. Satyrium nepalense (family: Orchidaceae) is a threatened terrestrial orchid species with valuable medicinal and nutritional properties. The survival of S. nepalense in wild conditions has been challenged by increasing global surface temperature. Hence, understanding the impact of climate change on its potential distribution is crucial to conserve and restore this species. In present study, Maxent species distribution modeling algorithm was used to simulate the current distribution of S. nepalense in India and predict the possible range shift in projected future climate scenarios. A set of 19 bioclimatic variables from WorldClim database were used to predict the potential suitable habitats in current climatic condition and four Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, and 8.5) scenarios by integrating five General Circulation Models (GCMs) for future distribution modeling of species for the years 2050 and 2070. Furthermore, change analysis was performed to identify the suitable habitat in current and future climate for delineating range expansion (gain), contraction (loss), and stable (no change) habitats of species. The Maxent model predicted that ~ 2.38% of the geographical area in India is presently climatically suitable for S. nepalense. The key bioclimatic variables affecting the distribution of studied species were the mean temperature of warmest quarter, mean temperature of wettest quarter, precipitation of warmest quarter, and temperature seasonality. Under future climate change scenarios, the total suitable habitat of S. nepalense will increase slightly in the Himalayan region and likely to migrate towards northward, but in the Western Ghats region, the suitable areas will be lost severely. The net habitat loss under four RCP scenarios was estimated from 26 to 39% for the year 2050, which could further increase from 47 to 60% by the year 2070. The finding of the predictive Maxent modeling approach indicates that warming climates could significantly affect the potential habitats of S. nepalense and hence suitable conservation measures need to be taken to protect this threatened orchid species in wild conditions.

Titel:	Modeling the effect of climate change on the distribution of threatened medicinal orchid Satyrium nepalense D. Don in India.
Autor/in / Beteiligte Person:	Kumar, D ; Rawat, S
Link:	Full Text Finder (Volltext)
Zeitschrift:	Environmental science and pollution research international, Jg. 29 (2022-10-01), Heft 48, S. 72431-72444
Veröffentlichung:	<2013->: Berlin : Springer ; <i>Original Publication</i>: Landsberg, Germany : Ecomed, 2022
Medientyp:	academicJournal
ISSN:	1614-7499 (electronic)
DOI:	10.1007/s11356-022-20412-w
Schlagwort:	Ecosystem Endangered Species India Climate Change Orchidaceae
Sonstiges:	Nachgewiesen in: MEDLINE Sprachen: English Publication Type: Journal Article Language: English [Environ Sci Pollut Res Int] 2022 Oct; Vol. 29 (48), pp. 72431-72444. <i>Date of Electronic Publication: </i>2022 May 07. MeSH Terms: Climate Change* ; Orchidaceae* ; Ecosystem ; Endangered Species ; India References: Abdelaal M, Fois M, Fenu G, Bacchetta G (2019) Using MaxEnt modeling to predict the potential distribution of the endemic plant Rosa arabica Crép. in Egypt. Ecol Inform 50:68–75. https://doi.org/10.1016/j.ecoinf.2019.01.003. (PMID: 10.1016/j.ecoinf.2019.01.003) ; Adhikari D, Reshi Z, Datta BK, Samant SS, Chettri A, Upadhaya K, Shah MA, Singh PP, Tiwary R, Majumdar K, Pradhan A, Thakur ML, Salam N, Zahoor Z, Mir MH, Kaloo ZA, Barik SK (2018) Inventory and characterization of new populations through ecological niche modelling improve threat assessment. Curr Sci 114(3):519–531. https://doi.org/10.18520/cs/v114/i03/519-531. (PMID: 10.18520/cs/v114/i03/519-531) ; Antúnez P, Suárez-Mota ME, Valenzuela-Encinas C, Ruiz-Aquino F (2018) The potential distribution of tree species in three periods of time under a climate change scenario. Forests 9(10):628. https://doi.org/10.3390/f9100628. (PMID: 10.3390/f9100628) ; Araújo MB, New M (2007) Ensemble forecasting of species distribution. Trends Ecol Evol 22:42–47. https://doi.org/10.1016/j.tree.2006.09.010. (PMID: 10.1016/j.tree.2006.09.010) ; Babbar SB, Singh DK (2016) Protocols for in vitro mass multiplication and analysis of medicinally important phenolics of a Salep orchid, Satyrium nepalense D. Don (“Salam Mishri”). In: Jain SM (ed) Protocols for In Vitro Cultures and Secondary Metabolite Analysis of Aromatic and Medicinal Plants, 2nd edn. Humana Press, New York, pp 1–11. ; Baek HJ, Lee J, Lee HS, Hyun YK, Cho C, Kwon WT, Marzin C, Gan SY, Kim MJ, Choi DH, Lee J (2013) Climate change in the 21st century simulated by HadGEM2-AO under Representative Concentration Pathways. Asia-Pac J Atmos Sci 49(5):603–618. https://doi.org/10.1007/s13143-013-0053-7. (PMID: 10.1007/s13143-013-0053-7) ; Barnosky AD, Matzke N, Tomiya S, Wogan G.O, Swartz B, Quental TB, …, Ferrer EA (2011) Has the Earth’s sixth mass extinction already arrived?. Nature 471(7336):51-57. ; Beaumont LJ, Esperón-Rodríguez M, Nipperess DA, Wauchope-Drumm M, Baumgartner JB (2019) Incorporating future climate uncertainty into the identification of climate change refugia for threatened species. Biol Conserv 237:230–237. https://doi.org/10.1016/j.biocon.2019.07.013. (PMID: 10.1016/j.biocon.2019.07.013) ; Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F (2012) Impacts of climate change on the future of biodiversity. Ecol Lett 15(4):365–377. https://doi.org/10.1111/j.1461-0248.2011.01736.x. (PMID: 10.1111/j.1461-0248.2011.01736.x) ; Chhabra T (2000) Satyrium nepalense D. Don in the upper Nilgiri plateau, with emphasis on its ethnobotanic link with the Toda tribals. Zoos’ Print J 16(1):408. (PMID: 10.11609/JoTT.ZPJ.16.1.408) ; Coban HO, Örücü ÖK, Arslan ES (2020) MaxEnt modeling for predicting the current and future potential geographical distribution of Quercus libani Olivier. Sustainability 12:2671–2680. https://doi.org/10.3390/su12072671. (PMID: 10.3390/su12072671) ; Collier MA, Jeffrey SJ, Rotstayn LD, Wong KK, Dravitzki SM, Moseneder C, Hamalainen C, Syktus JI, Suppiah R, Antony J, El Zein A (2011) The CSIRO-Mk3.6.0Atmosphere-Ocean GCM: participation in CMIP5 and data publication. In: 19 th International Congress on Modelling and Simulation, Perth, Australia, 12–16 December 2011. http://mssanz.org.au/modsim2011. ; Dhyani S, Kadaverugu R, Pujari P (2020) Predicting impacts of climate variability on Banj oak (Quercus leucotrichophora A. Camus) forests: understanding future implications for Central Himalayas. Reg Environ Chang 20:113. https://doi.org/10.1007/s10113-020-01696-5. (PMID: 10.1007/s10113-020-01696-5) ; Duffy KJ, Johnson SD (2017) Effects of distance from models on the fitness of floral mimics. Plant Biol 19:438–443. (PMID: 10.1111/plb.12555) ; Elith J, Kearney M, Phillips S (2010) The art of modelling range-shifting species. Methods Ecol Evol 1:330–342. https://doi.org/10.1111/j.2041-210X.2010.00036.x. (PMID: 10.1111/j.2041-210X.2010.00036.x) ; Elith J, Phillips SJ, Hastie T, Dudik M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57. https://doi.org/10.1111/j.1472-4642.2010.00725.x. (PMID: 10.1111/j.1472-4642.2010.00725.x) ; Fay MF (2018) Orchid conservation: how can we meet the challenges in the twenty-first century? Bot Stud 59(1):1–6. (PMID: 10.1186/s40529-018-0232-z) ; Fielding AH, Bell JFL (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24(1):38–49. https://doi.org/10.1017/S0376892997000088. (PMID: 10.1017/S0376892997000088) ; GBIF (2021) GBIF occurrences download. https://doi.org/10.15468/dl.7q9ea4 . Accessed on: 11 June 2021. ; Giri L, Jugran A, Rawat S, Dhyani P, Andola H, Bhatt ID, Rawal RS, Dhar U (2012) In vitro propagation, genetic and phytochemical assessment of Habenaria edgeworthii: an important Astavarga plant. Acta Physiol Plant 34(3):869–875. (PMID: 10.1007/s11738-011-0884-8) ; Giri L, Jugran AK, Bahukhandi A, Dhyani P, Bhatt ID, Rawal RS, Nandi SK, Dhar U (2017) Population genetic structure and marker trait associations using morphological, phytochemical and molecular parameters in Habenaria edgeworthii—a threatened medicinal orchid of West Himalaya, India. Appl Biochem Biotechnol 181(1):267–282. https://doi.org/10.1007/s12010-016-2211-8. (PMID: 10.1007/s12010-016-2211-8) ; Griffies SM, Winton M, Donner LJ, Horowitz LW, Downes SM, Farneti R, Gnanadesikan A, Hurlin WJ, Lee H, Liang Z, Palter JB, Samuels BL, Wittenberg AT, Wyman BL, Yin J, Zadeh N (2011) The GFDL CM3 coupled climate model: characteristics of the ocean and sea ice simulations. J Clim 24:3520–3544. https://doi.org/10.1175/2011JCLI3964.1. (PMID: 10.1175/2011JCLI3964.1) ; Habibullah S, Din BH, Tan SH, Zahid H (2021) Impact of climate change on biodiversity loss: global evidence. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-15702-8. (PMID: 10.1007/s11356-021-15702-8) ; Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978. https://doi.org/10.1002/joc.1276. (PMID: 10.1002/joc.1276) ; Hingane LS, Rupa Kumar K, Ramana Murty BV (1985) Long-term trends of surface air temperature in India. Int J Climatol 5(5):521–528. https://doi.org/10.1002/joc.3370050505. (PMID: 10.1002/joc.3370050505) ; Jacquemyn H, Waud M, Brys R, Lallemand F, Courty PE, Robionek A, Selosse MA (2017) Mycorrhizal associations and trophic modes in coexisting orchids: an ecological continuum between auto- and mixotrophy. Front Plant Sci 8:1497. https://doi.org/10.3389/fpls.2017.01497. (PMID: 10.3389/fpls.2017.01497) ; Khanum R, Mumtaz AS, Kumar S (2013) Predicting impacts of climate change on medicinal asclepiads of Pakistan using Maxent modelling. Acta Oecol 49:23–31. https://doi.org/10.1016/j.actao.2013.02.007. (PMID: 10.1016/j.actao.2013.02.007) ; Koch R, Almeida-Cortez JS, Kleinschmit B (2017) Revealing areas of high nature conservation importance in a seasonally dry tropical forest in Brazil: combination of modelled plant diversity hot spots and threat patterns. J Nat Conserv 35:24–39. https://doi.org/10.1016/j.jnc.2016.11.004. (PMID: 10.1016/j.jnc.2016.11.004) ; Kolanowska M, Rewicz A, Baranow P (2020) Ecological niche modeling of the pantropical orchid Polystachya concreta (Orchidaceae) and its response to climate change. Sci Rep 10:14801. https://doi.org/10.1038/s41598-020-71732-1. (PMID: 10.1038/s41598-020-71732-1) ; Kumar D, Singh M, Sharma S (2019) Fate of important medicinal plants in the eastern Himalaya in changing climate scenarios: a case of Panax pseudoginseng Wall. Appl Ecol Environ Res 17(6):13493–13511. https://doi.org/10.15666/aeer/1706_1349313511. (PMID: 10.15666/aeer/1706_1349313511) ; Kumar D, Rawat S, Joshi R (2021a) Predicting the current and future suitable habitat distribution of the medicinal tree Oroxylum indicum (L.) Kurz in India. J Appl Res Med Aromat Plants 23:100309. https://doi.org/10.1016/j.jarmap.2021.100309. (PMID: 10.1016/j.jarmap.2021.100309) ; Kumar D, Pandey A, Rawat S, Joshi M, Bajpai R, Upreti DK, Singh SP (2021b) Predicting the distributional range shifts of Rhizocarpon geographicum (L.) DC. in Indian Himalayan Region under future climate scenarios. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-15624-5. (PMID: 10.1007/s11356-021-15624-5) ; Kushwaha CP, Tripathi SK, Singh KP (2011) Tree specific traits affect flowering time in Indian dry tropical forest. Plant Ecol 212(6):985–998. https://doi.org/10.1007/s11258-010-9879-6. (PMID: 10.1007/s11258-010-9879-6) ; Lima DF, Mello JHF, Lopes IT, Forzza RC, Goldenberg R, Freitas L (2021) Phenological responses to climate change based on a hundred years of herbarium collections of tropical Melastomataceae. PLoS ONE 16(5):e0251360. https://doi.org/10.1371/journal.pone.0251360. (PMID: 10.1371/journal.pone.0251360) ; Lobo JM, Jiménez-Valverde A, Real R (2008) AUC: a misleading measure of the performance of predictive distribution models. Glob Ecol Biogeogr 17:145–151. https://doi.org/10.1111/j.1466-8238.2007.00358.x. (PMID: 10.1111/j.1466-8238.2007.00358.x) ; Mahendran G, Bai VN (2009) Mass propagation of Satyrium nepalense D. Don.—a medicinal orchid via seed culture. Sci Hortic 119(2):203–207. https://doi.org/10.1016/j.scienta.2008.07.029. (PMID: 10.1016/j.scienta.2008.07.029) ; McCormick MK, Jacquemyn H (2014) What constrains the distribution of orchid populations? New Phytol 202:392–400. https://doi.org/10.1111/nph.12639. (PMID: 10.1111/nph.12639) ; Medhi R, Chakrabarti S (2009) Traditional knowledge of NE people on conservation of wild orchids. Indian J Tradit Knowl 8:11–16. ; Mishra AP, Saklani S (2012) Satyrium nepalense: a rare medicinal orchid of western Himalaya (india); phytochemical screening, antimicrobial evaluation and conservation studies. Indones J Pharm 23(3):162–170. https://doi.org/10.14499/indonesianjpharm23iss3pp162-170. (PMID: 10.14499/indonesianjpharm23iss3pp162-170) ; Mishra AP, Saklani S, Salehi B, Parcha V, Sharifi-Rad M, Milella L, Iriti M, Sharifi-Rad J, Srivastava M (2018) Satyrium nepalense, a high altitude medicinal orchid of Indian Himalayan region: chemical profile and biological activities of tuber extracts. Cell Mol Biol 64(8):35–43. https://doi.org/10.14715/cmb/2018.64.8.6. (PMID: 10.14715/cmb/2018.64.8.6) ; Mohandass D (2008) Floristic distribution in montane swamps of the Nilgiri Mountains, Southern India. Int J Ecol Environ Sci 34(1):55–62. ; Morris WF, Ehrlén J, Dahlgren JP, Loomis AK, Louthan AM (2020) Biotic and anthropogenic forces rival climatic/abiotic factors in determining global plant population growth and fitness. Proc Natl Acad Sci 117(2):1107–1112. https://doi.org/10.1073/pnas.1918363117. (PMID: 10.1073/pnas.1918363117) ; Nagahama N, Bonino MF (2020) Modeling the potential distribution of Valeriana carnosa Sm. in Argentinean Patagonia: a proposal for conservation and in situ cultivation considering climate change projections. J Appl Res Med Aromat Plants 16:100240. https://doi.org/10.1016/j.jarmap.2020.100240. (PMID: 10.1016/j.jarmap.2020.100240) ; Nilsson AL (1992) Orchid pollination biology. Trends Ecol Evol 7(8):255–259. (PMID: 10.1016/0169-5347(92)90170-G) ; O'Donnell MS, Ignizio DA (2012) Bioclimatic predictors for supporting ecological applications in the conterminous United States: U.S. Geological Survey Data Series, 691, pp 10. https://pubs.usgs.gov/ds/691/ds691.pdf. ; Opedal OH, Armbruster WS, Graae BJ (2015) Linking small-scale topography with microclimate plant species diversity and intra-specific trait variation in an alpine landscape. Plant Ecol Divers 8:305–315. https://doi.org/10.1080/17550874.2014.987330. (PMID: 10.1080/17550874.2014.987330) ; Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, …, van Ypserle JP (2014) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, pp 151. ; Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371. https://doi.org/10.1046/j.1466-822X.2003.00042.x. (PMID: 10.1046/j.1466-822X.2003.00042.x) ; Pearson RG, Dawson TP, Liu C (2004) Modelling species distributions in Britain: a hierarchical integration of climate and land-cover data. Ecography 27:285–298. https://doi.org/10.1111/j.0906-7590.2004.03740.x. (PMID: 10.1111/j.0906-7590.2004.03740.x) ; Pearson RG, Raxworthy CJ, Nakamura M, Peterson AT (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34:102–117. https://doi.org/10.1111/j.1365-2699.2006.01594.x. (PMID: 10.1111/j.1365-2699.2006.01594.x) ; Pellegrino G, Luca A, Bellusci F (2016) Relationships between orchid and fungal biodiversity: mycorrhizal preferences in Mediterranean orchids. Plant Biosyst 150(2):180–189. https://doi.org/10.1080/11263504.2014.940071. (PMID: 10.1080/11263504.2014.940071) ; Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modelling of species geographic distributions. Ecol Model 190:231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026. (PMID: 10.1016/j.ecolmodel.2005.03.026) ; Phillips SJ, Dudik M (2008) Modelling 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. (PMID: 10.1111/j.0906-7590.2008.5203.x) ; Qin AL, Liu B, Guo QS, Bussmann RW, Ma FQ, Jian ZJ, Xu GX, Pei SX (2017) MaxEnt modeling for predicting impacts of climate change on the potential distribution of Thuja sutchuenensis Franch., an extremely endangered conifer from southwestern China. Glob Ecol Conserv 10:139–146. https://doi.org/10.1016/j.gecco.2017.02.004. (PMID: 10.1016/j.gecco.2017.02.004) ; Rajpoot R, Adhikari D, Verma S, Saikia P, Kumar A, Grant KR, Datanandan A, Kumar A, Khare PK, Khan ML (2020) Climate models predict a divergent future for the medicinal tree Boswellia serrata Roxb. in India. Glob Ecol Conserv 23:e01040. https://doi.org/10.1016/j.gecco.2020.e01040. (PMID: 10.1016/j.gecco.2020.e01040) ; Rao NA (2004) Medicinal orchid wealth of Arunachal Pradesh newsletter of Envis. Indian Med Plants 1:1–10. ; Raskoti BB, Kurzweil H, Pant B, Teoh ES, Ale R, Amatya G, Bussmann RW (2021) Satyrium nepalense D. Don. Satyrium nepalense var. ciliatum (Lindl.) Hook. f. Orchidaceae. In: Kunwar RM, Sher H, Bussmann RW (eds) Ethnobotany of the Himalayas, Ethnobotany of Mountain Regions, Springer Nature, Switzerland. ; Reiter N, Lawrie AC, Linde CC (2018) Matching symbiotic associations of an endangered orchid to habitat to improve conservation outcomes. Ann Bot 122:947–959. https://doi.org/10.1093/aob/mcy094. (PMID: 10.1093/aob/mcy094) ; Sahoo AK, Ansari AA (2007) Notes on a threatened orchid (Satyrium Sw.) in Sikkim Himalaya. ENVIS Quart Newslett 1:4–5. ; Shcheglovitova M, Anderson RP (2013) Estimating optimal complexity for ecological niche models: a jackknife approach for species with small sample sizes. Ecol Model 269:9–17. https://doi.org/10.1016/j.ecolmodel.2013.08.011. (PMID: 10.1016/j.ecolmodel.2013.08.011) ; Spiers JA, Oatham MP, Rostant LV, Farrell AD (2018) Applying species distribution modelling to improving conservation based decisions: a gap analysis of Trinidad and Tobago’s endemic vascular plants. Biodivers Conserv 27(11):2931–2949. https://doi.org/10.1007/s10531-018-1578-y. (PMID: 10.1007/s10531-018-1578-y) ; Swets J (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293. https://doi.org/10.1126/science.3287615. (PMID: 10.1126/science.3287615) ; Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, Collingham YC, Erasmus BFN, Ferreira De Siqeira M, Grainger A, Hannah L, Hughes L, Huntley B, Van Jaarsveld AS, Midgley GF, Miles L, Ortega-Huertas MA, Peterson AT, Phillips OL, Williams SE (2004) Extinction risk from climate change. Nature 427:145–148. https://doi.org/10.1038/nature02121. (PMID: 10.1038/nature02121) ; Tupac OJ, Ackerman JD, Bayman P (2002) Diversity and host specifcity of endophytic Rhizoctonia-like fungi from tropical orchids. Am J Bot 89(11):1852–1858. (PMID: 10.3732/ajb.89.11.1852) ; Wang T, Campbell EM, O’Neill GA, Aitken SN (2012) Projecting future distributions of ecosystem climate niches: uncertainties and management applications. For Ecol Manag 279:128–140. https://doi.org/10.1016/j.foreco.2012.05.034. (PMID: 10.1016/j.foreco.2012.05.034) ; Wani AM, Raj AJ, Kanwar M (2013) Impact of climate change on forests of Eastern Himalayas and adaptation strategies for combating it. Int J Agric For 3(3):98–104. ; Watanabe S, Hajima T, Sudo K, Nagashima T, Takemura T, Okajima H, Nozawa T, Kawase H, Abe M, Yokohata T, Ise T, Sato H, Kato E, Takata K, Emori S, Kawamiya M (2011) MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments. Geosci Model Dev 4:845–872. https://doi.org/10.5194/gmd-4-845-2011. (PMID: 10.5194/gmd-4-845-2011) ; Wilson CD, Roberts D, Reid N (2011) Applying species distribution modeling to identify areas of high conservation value for endangered species: a case study using Margaritifera margaritifera (L.). Biol Conserv 144:821–829. (PMID: 10.1016/j.biocon.2010.11.014) ; Wraith J, Pickering C (2018) Quantifying anthropogenic threats to orchids using the IUCN Red List. Ambio 47(3):307–317. (PMID: 10.1007/s13280-017-0964-0) ; Yang XQ, Kushwaha SPS, Saran S, Xu J, Roy PS (2013) Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L.: in Lesser Himalayan foothills. Ecol Eng 51:83–87. (PMID: 10.1016/j.ecoleng.2012.12.004) ; Yi YJ, Cheng X, Yang ZF, Zhang SH (2016) MaxEnt modeling for predicting the potential distribution of endangered medicinal plant (H. riparia Lour) in Yunnan, China. Ecol Eng 92:260–269. https://doi.org/10.1016/j.ecoleng.2016.04.010. (PMID: 10.1016/j.ecoleng.2016.04.010) ; Yukimoto S, Adachi Y, Hosaka M, Sakami T, Yoshimura H, Hirabara M, Tanaka TY, Shindo E, Tsujino H, Deushi M, Mizuta R, Yabu S, Obata A, Nakano H, Koshiro T, Ose T, Kitoh A (2012) A new Global Climate Model of the Meteorological Research Institute: MRI-CGCM3—model description and basic performance. J Meteorol Soc Japan 90A:23–64. https://doi.org/10.2151/jmsj.2012-A02. (PMID: 10.2151/jmsj.2012-A02) Contributed Indexing: Keywords: Climate change; Maxent; Medicinal plant; Orchids; Satyrium nepalense; Species distribution modeling; Threatened plant Entry Date(s): Date Created: 20220507 Date Completed: 20221216 Latest Revision: 20221216 Update Code: 20240513

Klicken Sie ein Format an und speichern Sie dann die Daten oder geben Sie eine Empfänger-Adresse ein und lassen Sie sich per Email zusenden.

BibTeX Citavi, JabRef, u.a.
(Literaturverwaltung)

PDF kein Volltext!
(Merkzettel, Notizen)

RIS Endnote, Citavi u.a.
(Literaturverwaltung)

MODS
(XML zur Weiterverarbeitung)

oder

Wählen Sie das für Sie passende Zitationsformat und kopieren Sie es dann in die Zwischenablage, lassen es sich per Mail zusenden oder speichern es als PDF-Datei.

Gewünschter Zitations-Stil:

oder

Bitte prüfen Sie, ob die Zitation formal korrekt ist, bevor Sie sie in einer Arbeit verwenden. Benutzen Sie gegebenenfalls den "Exportieren"-Dialog, wenn Sie ein Literaturverwaltungsprogramm verwenden und die Zitat-Angaben selbst formatieren wollen.

Modeling the effect of climate change on the distribution of threatened medicinal orchid Satyrium nepalense D. Don in India.