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Distribution of rose hip (Rosa canina L.) under current and future climate conditions

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Abstract

This study aims to model the potential distribution areas of the species Rosa canina L. (rose hip) and to predict and analyse possible future changes in its distribution under given climate change scenarios. Nineteen bioclimatic variables from the WorldClim database were applied to 180 known species presence locations and the potential distribution area of the species under current conditions was identified using MaxEnt. To determine the future geographical distribution of the species under the impact of climate change, the Community Climate System Model (CCSM ver. 4) was used. The climate change scenarios were taken from the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios for 2050 and 2070 developed in line with the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In addition, change analysis was carried out to identify the precise differences of area and location between the current and future potential distributions of the species, specifying habitat gains, habitat losses and stable habitats. Finally, a jackknife test was carried out to determine which individual bioclimatic variables affect the geographical distribution of the species the most. The study found that areas totalling 170,596 km2 are currently ‘highly suitable’ for Rosa canina L., but that this area will contract to 114,474 km2 by 2070 in the RCP 4.5 scenario and to 41,146 km2 by 2070 in the RCP 8.5 scenario. The mean temperature of the wettest quarter was the most influential bioclimatic variable affecting the distribution of the species.

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References

  • Adhikari D, Barik S, Upadhaya K (2012) Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India. Ecol Eng 40:37–43. https://doi.org/10.1016/j.ecoleng.2011.12.004

    Article  Google Scholar 

  • Akkemik Ü (2014) Türkiye’nin Doğal-Egzotik Ağaç ve Çalıları I. Orman Genel Müdürlüğü Yayınları, Ankara

    Google Scholar 

  • Akyol A, Örücü ÖK (2019a) Investigation of cornelian cherry (Cornus mas L.) in the scope of non-wood forest products according to climate change scenarios and species distribution model. Eur J Sci Technol 17:224–233. https://doi.org/10.31590/ejosat.615019

    Article  Google Scholar 

  • Akyol A, Örücü ÖK (2019b) Investigation and evaluation of stone pine (Pinus pinea L.) current and future potential distribution under climate change in Turkey. CERNE 25(4):415–423. https://doi.org/10.1590/01047760201925042643

    Article  Google Scholar 

  • Al-Qaddi N, Vessella F, Stephan J, Al-Eisawi D, Schirone B (2017) Current and future suitability areas of kermes oak (Quercus coccifera L.) in the Levant under climate change. Reg Environ Chang 17:143–156. https://doi.org/10.1007/s10113-016-0987-2

    Article  Google Scholar 

  • Arslan ES (2019) İklim değişimi senaryoları ve tür dağılım modeline göre kentsel yol ağaçlarının ekosistem hizmetleri bağlamında değerlendirilmesi: Robinia pseudoacacia L. örneği. Türkiye Ormancılık Dergisi 20:142–148. https://doi.org/10.18182/tjf.559883

    Article  Google Scholar 

  • Ashraf U, Ali H, Chaudry MN, Ashraf I, Batool A, Saqib Z (2016) Predicting the potential distribution of Olea ferruginea in Pakistan incorporating climate change by using MaxEnt model. Sustainability 8:1–11. https://doi.org/10.3390/su8080722

    Article  Google Scholar 

  • Barnosky AD, Matzke N, Tomiya S, Wogan GOU, Swartz B, Quental TB, Marshall C, McGuire JL, Lindsey EL, Maguire KC, Mersey B, Ferrer EA (2011) Has the Earth’s sixth mass extinction already arrived? Nature 471:51–57. https://doi.org/10.1038/nature09678

    Article  CAS  Google Scholar 

  • Bertrand R, Lenoir J, Piedallu C, Riofrío-Dillon G, de Ruffray P, Vidal C, Pierrat J-C, Gégout J-C (2011) Changes in plant community composition lag behind climate warming in lowland forests. Nature 479:517–520. https://doi.org/10.1038/nature10548

    Article  CAS  Google Scholar 

  • Booth TH (2018) Why understanding the pioneering and continuing contributions of BIOCLIM to species distribution modelling is important. J Aust Ecol 43:852–860. https://doi.org/10.1111/aec.12628

    Article  Google Scholar 

  • Booth TH, Nix HA, Busby JR, Hutchinson MF (2014) BIOCLIM: the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Divers Distrib 20:1–9. https://doi.org/10.1111/ddi.12144

    Article  Google Scholar 

  • Brito JC, Acosta AL, Álvares F, Cuzin F (2009) Biogeography and conservation of taxa from remote regions: an application of ecological-niche based models and GIS to North-African canids. Biol Conserv 142:3020–3029. https://doi.org/10.1016/j.biocon.2009.08.001

  • CESM (2019) Community earth system model CCSM4.0 public release. http://www.cesm.ucar.edu/models/ccsm4.0/. Accessed 20 June 2019

  • Coban HO, Koc A, Eker M (2010) Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black sea region-a case study. J Environ Biol 31:169–178

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Cobben MMP, van Treuren R, Castaneda-Alvarez NP, Khoury CK, Kik C, Van Hintum TJL (2015) Robustness and accuracy of MaxEnt niche modelling for Lactuca species distributions in light of collecting expeditions. Plant Genet Resour 13:153–161. https://doi.org/10.1017/S1479262114000847

    Article  Google Scholar 

  • Davis PH (1984) In: David PH (ed) Flora of Turkey and The Aegean Islands - VIII, vol 8. Edinburgh University Press, Edinburgh

    Google Scholar 

  • Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40:677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159

  • Field A (2013) Discovering statistics using IBM SPSS statistics. SAGE Publications

  • Fitzpatrick MC, Gove AD, Sanders NJ, Dunn RR (2008) Climate change, plant migration, and range collapse in a global biodiversity hotspot: the Banksia (Proteaceae) of Western Australia. Glob Chang Biol 14:1337–1352. https://doi.org/10.1111/j.1365-2486.2008.01559.x

    Article  Google Scholar 

  • Gassó N, Thuiller W, Pino J, Vilà M (2012) Potential distribution range of invasive plant species in Spain. NeoBiota 12:25–40. https://doi.org/10.3897/neobiota.12.2341

    Article  Google Scholar 

  • Gaston KJ (1996) Species richness: measure and measurement. In: Biodiversity: a biology of numbers and difference. Blackwell Science, Oxford, pp 77–113

    Google Scholar 

  • GBIF (2020) Rosa canina L. in GBIF Secretariat. GBIF Backbone Taxonomy. Checklist dataset. https://doi.org/10.15468/39omei. Accessed via GBIF.org on 2020-04-01

  • Güner ŞT, Özkan K, Çömez A (2011) Key factors in the site selection of Rosa canina (L.) applying the generalized additive model. Pol J Ecol 59(3):475–482

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Hosmer DW, Lemeshow S, Sturdivant RX (2013) Applied logistic regression, vol 398. John Wiley & Sons

  • Hughes L (2000) Biological consequences of global warming: is the signal already apparent? Trends Ecol Evol 15(2):56–61. https://doi.org/10.1016/S0169-5347(99)01764-4

    Article  CAS  Google Scholar 

  • Hunt LP, Petty S, Cowley R, Fisher A, Ash AJ, MacDonald N (2007) Factors affecting the management of cattle grazing distribution in northern Australia: preliminary observations on the effect of paddock size and water points. Rangeland J 29:169–179. https://doi.org/10.1071/RJ07029

    Article  Google Scholar 

  • Ibáñez I, Katz DSW, Peltier D, Wolf SM, Barrie BTC (2014) Assessing the integrated effects of landscape fragmentation on plants and plant communities: the challenge of multiprocess–multiresponse dynamics. J Ecol 102:882–895. https://doi.org/10.1111/1365-2745.12223

    Article  Google Scholar 

  • İlisulu K (1992) İlaç ve Baharat Bitkileri. AÜZF Yayınevi, Ankara

  • IPCC (2013) In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) 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 University Press, Cambridge, p 1535

    Google Scholar 

  • Jürgens AH, Seitz B, Kowarik I (2007) Genetic differentiation of Rosa canina (L.) at regional and continental scales. Plant Syst Evol 269:39–53. https://doi.org/10.1007/s00606-007-0569-3

    Article  Google Scholar 

  • Karakaya T (2016) Gaziantep yöresi Nur Dağı'nda Kuşburnu (Rosa canina L.)'nun ekolojik özellikleri ile potansiyel dağılım modellemesi ve haritalanması. Doctoral Dissertation, Anadolu University

  • Karataş R, Şentürk Ö, Arslan M, Güner D, Negiz MG, Özkan K (2019) Potential distribution of some non-wood forest products in the Turkmen Mountain. Turk J For Res 6(1):15–28. https://doi.org/10.17568/ogmoad.424010

    Article  Google Scholar 

  • Karatepe Y (2006) Kuşburnu (Rosa canina L.)'nun Eğirdir gölü havzasındaki doğal yayılış alanlarına ait bazı ekolojik özellikler. 1. Uluslararası Odun Dışı Orman Ürünleri Sempozyumu. 1-4 November 2006, Karadeniz Teknik University Publishing

  • Kazaz G (2013) Sütçüler yöresinde kuşburnu (Rosa canina L.) türünün coğrafi dağılım modellemesi. Dissertation, Süleyman Demirel University, Isparta

  • Kharazmi A, Winther K, Rein E (2000) Rose-hip formulations as anti-inflammatory natural medicine for alleviating/reducing symptoms associated with inflammation and arthritis US Patent number 6024960

  • Koçan N (2010) Peyzaj planlama ve tasarım çalışmalarında kuşburnu (Rosa canina L.) bitkisinin değerlendirilmesi. Harran Üniversitesi Ziraat Fakültesi Dergisi 14(4):33–37

    Google Scholar 

  • Kostic S (1994) Nutritive value of rose hips and its usability in baby food vitaminization. Rev Res Work Fac Agric 39: 67–71

  • Kühn BF (1992) Hyben. Dyrkning Og Anvendelse. Gron Viden 69:1–6

    Google Scholar 

  • Lawler JJ, Shafer SL, White D, Kareiva P, Maurer EP, Blaustein AR, Bartlein PJ (2009) Projected climate induced faunal change in the Western Hemisphere. Ecology 90:588–597. https://doi.org/10.1890/08-0823.1

  • Lenoir J, Gégout JC, Marquet P, De Ruffray P, Brisse HJS (2008) A significant upward shift in plant species optimum elevation during the 20th century. Science 320:1768–1771. https://doi.org/10.1126/science.1156831

    Article  CAS  Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756. https://doi.org/10.1038/nature08823

    Article  CAS  Google Scholar 

  • Nilson Ö (1972) Flora of Turkey and Tisst Aegean Islands. In: P.H. Davis (ed) 4, Edinburgh Univ. Press, Edinburgh, pp 106–128

  • Örücü ÖK (2019) Phoenix theophrasti Gr.’nin iklim değişimine bağlı günümüz ve gelecekteki yayılış alanlarının MaxEnt modeli ile tahmini ve bitkisel tasarımda kullanımı. Turk J For 20:274–283. https://doi.org/10.18182/tjf.613205

    Article  Google Scholar 

  • Özkan K, Bilir N (2008) Influence of soil and topographical characteristics on spatial distribution of wild rosa (Rosa canina L.) and its indicator species in Beysehir watershed, Mediterrian region Turkey. J Malay For 71:87–96

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Peterson AT, Papes M, Eaton M (2007) Transferability and model evaluation in ecological niche modeling: a comparison of GARP and MaxEnt. Ecography 30(4):550–560. https://doi.org/10.1111/j.2007.0906-7590.05102.x

    Article  Google Scholar 

  • Phillips SJ, Dudik 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

    Article  Google Scholar 

  • Phillips SJ, Elith J (2010) POC plots: calibrating species distribution models with presence-only data. Ecology 91(8):2476–2484. https://doi.org/10.1890/09-0760.1

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026

    Article  Google Scholar 

  • Phillips SJ, Anderson RP, Dudík M, Schapire RE, Blair ME (2017) Opening the black box: an open-source release of MaxEnt. Ecography 40:887–893. https://doi.org/10.1111/ecog.03049

    Article  Google Scholar 

  • QGIS (2019) QGis 3.10 Zanzibar - A Free and Open GIS. https://qgis.org/tr/site/forusers/download.html. Accessed 20 June 2019

  • QGIS.org (2020) QGIS Geographic Information System. Open Source Geospatial Foundation Project. http://qgis.org

  • 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

    Article  Google Scholar 

  • Raxworthy CJ, Pearson RG, Rabibisoa N, Rakotondrazafy AM, Ramanamanjato JB, Raselimanana AP, Wu S, Nussbaum RA, Stone DA (2008) Extinction vulnerability of tropical montane endemism from warming and upslope displacement: a preliminary appraisal for the highest massif in Madagascar. Glob Chang Biol 14(8):1703–1720. https://doi.org/10.1111/j.1365-2486.2008.01596.x

    Article  Google Scholar 

  • Remya K, Ramachandran A, Jayakumar S (2015) Predicting the current and future suitable habitat distribution of Myristica dactyloides Gaertn. Using MaxEnt model in the Eastern Ghats, India. Ecol Eng 82:184–188. https://doi.org/10.1016/j.ecoleng.2015.04.053

    Article  Google Scholar 

  • Salman-Özen M (2013) Bolu Merkez İlçesinde Kuşburnu (Rosa spp.) Genetik Kaynaklarının Seleksiyonu ve Antioksidan Aktivitelerinin Tespiti. Dissertation, Selçuk University

  • 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

    Article  Google Scholar 

  • Thuiller W, Lavorel S, Araujo MB, Sykes MT, Prentice C (2005) Climate change threats to plant diversity in Europe. Proc Natl Acad Sci U S A 102:8245–8250. https://doi.org/10.1073/pnas.0409902102

    Article  CAS  Google Scholar 

  • Tittensor DP, Baco AR, Brewin PE, Clark MR, Consalvey M, Hall-Spencer J, Rowden AA, Schlacher T, Stocks KI, Rogers AD (2009) Predicting global habitat suitability for stony corals on seamounts. J Biogeogr 36:1111–1128. https://doi.org/10.1111/j.1365-2699.2008.02062.x

    Article  Google Scholar 

  • Tsoar A, Allouche O, Steinitz O, Rotem D, Kadmon R (2007) A comparative evaluation of presence-only methods for modelling species distribution. Divers Distrib 13:397–405. https://doi.org/10.1111/j.1472-4642.2007.00346.x

    Article  Google Scholar 

  • User ET (1967) Memleketimizde Orta ve Kuzey Anadolu’da yetişen kuşburnunun C vitamini bakımından durumu, bununla ilgili halk gelenekleri hakkında bir araştırma. Türk Hijyen ve Tecrübi Biyoloji Dergisi 27(1):39–60

    CAS  Google Scholar 

  • Walden-Schreiner C, Leung YF, Kuhn T, Newburger T, Tsai WL (2017) Environmental and managerial factors associated with pack stock distribution in high elevation meadows: Case study from Yosemite National Park. Journal of environmental management, 193:52–63. https://doi.org/10.1016/j.jenvman.2017.01.076

  • Wang Y, Xie B, Wan F, Xiao Q, Dai L (2007) Application of ROC curve analysis in evaluating the performance of alien species potential distribution models. Biodivers Sci 15:365–372. https://doi.org/10.1360/biodiv.060280

    Article  Google Scholar 

  • Ward DF (2007) Modelling the potential geographic distribution of invasive ant species in New Zealand. Biol Invasions 9:723–735. https://doi.org/10.1007/s10530-006-9072-y

    Article  Google Scholar 

  • Wei B, Wang RL, Hou K, Wang XY, Wu W (2018) Predicting the current and future cultivation regions of Carthamus tinctorius L. using MaxEnt model under climate change in China. Glob Ecol Conserv 16:e00477. https://doi.org/10.1016/j.gecco.2018.e00477

    Article  Google Scholar 

  • Wollan AK, Bakkestuen V, Kauserud H, Gulden G, Halvorsen R (2008) Modelling and predicting fungal distribution patterns using herbarium data. J Biogeogr 35:2298–2310. https://doi.org/10.1111/j.1365-2699.2008.01965.x

    Article  Google Scholar 

  • WorldClim (2019) WorldClim - global climate data. www.worldclim.org. Accessed 20 June 2019

  • Yalçın S (2012) Modeling the current and future ranges of Turkish Pine (Pinus brutia) and Oriental Beech (Fagus orientalis) in Turkey in the face of climate change. Dissertation, Middle East Technical University

  • 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

    Article  Google Scholar 

  • Yılmaz H, Bulut Y, Kelkit A (1996) Peyzaj planlama çalışmalarında Rosa canina (Kuşburnu)’nın kullanım alanları. Kuşburnu Sempozyumu. 5–6 September 1996, Gümüşhane

  • Yuan HS, Wei YL, Wang XG (2015) MaxEnt modeling for predicting the potential distribution of Sanghuang, an important group of medicinal fungi in China. Fungal Ecol 17:140–145. https://doi.org/10.1016/j.funeco.2015.06.001

    Article  Google Scholar 

  • Zhang K, Yao L, Meng J, Tao J (2018) MaxEnt modeling for predicting the potential geographical distribution of two peony species under climate change. Sci Total Environ 634:1326–1334. https://doi.org/10.1016/j.scitotenv.2018.04.112

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Landscape Architecture, Faculty of Architecture, Süleyman Demirel University, Isparta, Turkey

    E. Seda Arslan & Ömer K. Örücü

  2. Department of Forest Engineering, Faculty of Forestry, İzmir Kâtip Çelebi University, İzmir, Turkey

    Ayhan Akyol

  3. Department of Forest Engineering, Faculty of Forestry,, Bursa Technical University, Bursa, Turkey

    Ayşe Gül Sarıkaya

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  1. E. Seda Arslan
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Arslan, E.S., Akyol, A., Örücü, Ö.K. et al. Distribution of rose hip (Rosa canina L.) under current and future climate conditions. Reg Environ Change 20, 107 (2020). https://doi.org/10.1007/s10113-020-01695-6

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