Article

Article name BIOCLIMATIC FACTORS LIMITING THE DISTRIBUTION OF IRIS SIBIRICA ACROSS EURASIA
Authors

Rustam H. Pshegusov, PhD, Head of the Forest Ecosystem Monitoring Laboratory in the Tembotov Institute of Ecology of Mountain Territories of RAS (360051, Russia, Kabardino-Balkar Republic, Nalchik, I. Armand street, 37-a); iD ORCID: https://orcid.org/0000-0002-6204-2690; е-mail: p_rustem@inbox.ru
Victoria A. Chadaeva, Dr.Sc., Head of the Geobotanical Research Laboratory in the Tembotov Institute of Ecology of Mountain Territories of RAS (360051, Russia, Kabardino- Balkar Republic, Nalchik, I. Armand street, 37-a); iD ORCID: https://orcid.org/0000-0002-0788-1395; е-mail: v_chadayeva@mail.ru
Larisa M. Abramova, Dr.Sc., Head of the Flora and Vegetation Laboratory in the South-Ural Botanical Garden-Institute of Ufa Federal Scientific Centre of RAS (450080, Russia, Republic of Bashkortostan, Ufa, Mendeleyeva street, 195/3); iD ORCID: https://orcid.org/0000-0002-3196-2080; e-mail: abramova57lm@yandex.ru

Reference to article

Pshegusov R.H., Chadaeva V.A., Abramova L.M. 2025. Bioclimatic factors limiting the distribution of Iris sibirica across Eurasia. Nature Conservation Research 10(3): 54–70. https://dx.doi.org/10.24189/ncr.2025.017

Electronic Supplement 1. Manipulation and evaluation of input data for the paper by Pshegusov et al. (2025) (Link)
Electronic Supplement 2. Iris sibirica populations in ecological and geographic spaces (Link)
Electronic Supplement 3. Principal component analysis of abiotic variables in Iris sibirica habitats (Link)

Section Research articles
DOI https://dx.doi.org/10.24189/ncr.2025.017
Abstract

With a wide range in Eurasia, Iris sibirica has an irregular distribution pattern and is listed in regional and national Red Data Books and on Red Lists of many countries in Europe and Asia. The abiotic causes of the species rarity (bioclimatic limiting factors) and adaptations in different parts of its range are still poorly understood. The formalisation of I. sibirica's ecological niches in the n-dimensional space of environmental factors will clarify these issues. We hypothesised that the ecological niches of I. sibirica were differentiated in the European and Asian parts of its range, allowing the species to adapt under diverse environmental conditions of plain and mountain habitats. This study aimed to (1) identify abiotic boundaries for various parts of the I. sibirica range in Eurasia (i.e. population groups), (2) test whether the ecological niches of Eurasian population groups were differentiated in environmental space, (3) provide information on environmental reasons of the species rarity in various parts of the range. To test whether the ecological niches of I. sibirica overlapped in various parts of its range, we applied the kernel density estimation method for niche visualisation in PCA (Principal Component Analysis) axis space. We have also used quantitative niche overlap metrics such as Schoener's D, Hellinger's I and COUE (Centroid shift, Overlap (Stability), Unfilling, Expansion). WorldClim bioclimatic variables were used to formalise the temperature and precipitation components of ecological niches. By a non-hierarchical iterative k-means clustering of abiotic variables in presence points, West European (463 points), East European-Siberian (186 points) and Mountain (112 points) population groups of I. sibirica were distinguished. In terms of temperature and precipitation parameters, the Mountain population habitats were similar to those of the West European populations (Stability of 0.90–0.99), but clearly differed from habitats of the East European-Siberian populations (Expansion of 0.85–1.00). In both cases, the ecological niche of the Mountain population group was clearly wider in the precipitation component. This is probably due to the relatively humid climate and orographic heterogeneity of mountainous areas, which enables I. sibirica to occupy sites with a wide range of precipitation but suitable moisture availability (e.g. couloirs, microrelief depressions). The ecological niches of the West European and East European-Siberian populations clearly differed by temperature component, but overlapped by precipitation component in the environmental space of PCA axes. Schener's D and Hellinger's I values were ranged from 0.02 to 0.21 for temperature variables and from 0.24 to 0.71 for precipitation variables. For the East European-Siberian population group, Unfilling in the temperature component of niche was 0.84–0.88. Thus, I. sibirica is adaptable to a wide range of temperature conditions in Eurasia, but has a narrow specialisation in moisture availability and is limited in suitable habitats (e.g. wet, swampy and marshy meadows), especially in the more continental and less humid East European-Siberian part of its range.

Keywords

ecological niche models, kernel density estimation, niche overlap metrics, population groups, species distribution

Artice information

Received: 10.02.2025. Revised: 20.06.2025. Accepted: 26.07.2025.

The full text of the article
References

Aiello-Lammens M.E., Boria R.A., Radosavljevic A., Vilela B., Anderson R.P. 2015. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38(5): 541–545. DOI: 10.1111/ecog.01132
Alexeyeva N.B. 2008. Genus Iris L. (Iridaceae) in the Russia. Turczaninowia 11(2): 5–68. [In Russian]
Allouche O., Tsoar A., Kadmon R. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (tss). Journal of Applied Ecology 43(6): 1223–1232. DOI: 10.1111/j.1365-2664.2006.01214.x
Atwater D.Z., Ervine C., Barney J.N. 2018. Climatic niche shifts are common in introduced plants. Nature Ecology and Evolution 2(1): 34–43. DOI: 10.1038/s41559-017-0396-z
Banerjee A.K., Mukherjee A., Guo W., Ng W.L., Huang Y. 2019. Combining ecological niche modeling with genetic lineage information to predict potential distribution of Mikania micrantha Kunth in South and Southeast Asia under predicted climate change. Global Ecology and Conservation 20: e00800. DOI: 10.1016/j.gecco.2019.e00800
Beksheneva L.F., Reut A.A. 2020. Water regime of some representatives of the genus Iris L. during introduction in the Southern Urals. Ekosistemy 22: 82–89. DOI: 10.37279/2414-4738-2020-22-82-89 [In Russian]
Blonder B., Lamanna C., Violle C., Enquist B.J. 2014. The n-dimensional hypervolume. Global Ecology and Biogeography 23(5): 595–609. DOI: 10.1111/geb.12146
Boltenkov E., Artyukova E., Kozyrenko M., Erst A., Trias-Blasi A. 2020. Iris sanguinea is conspecific with I. sibirica (Iridaceae) according to morphology and plastid DNA sequence data. PeerJ 8: e10088. DOI: 10.7717/peerj.10088
Botta-Dukát Z., Chytrý M., Hájková P., Havlová M. 2005. Vegetation of lowland wet meadows along a climatic continentality gradient in Central Europe. Preslia 77(1): 89–111.
Broennimann O., Fitzpatrick M.C., Pearman P.B., Petitpierre B., Pellissier L., Yoccoz N.G., Thuiller W., Fortin M.J., Randin C., Zimmermann N.E., Graham C.H., Guisan A. 2012. Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography 21(4): 481–497. DOI: 10.1111/j.1466-8238.2011.00698.x
Cotado A., Munné-Bosch S. 2020. Distribution, trade-offs and drought vulnerability of a high-mountain Pyrenean endemic plant species, Saxifraga longifolia. Global Ecology and Conservation 22: e00916. DOI: 10.1016/j.gecco.2020.e00916
Davidson I. 2002. Understanding k-means non-hierarchical clustering. SUNY Albany – Technical Report 2: 2–14.
Elith J., Franklin J. 2013. Species distribution modeling. In: S.A. Levin (Ed.): Encyclopedia of Biodiversity (Second Edition). Vol. 6. Oxford: Academic Press. P. 692–705.
Elith J., Phillips S.J., Hastie T., Dudík M., Chee Y.E., Yates C.J. 2011. A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17(1): 43–57. DOI: 10.1111/j.1472-4642.2010.00725.x
Ellenberg H., Weber H.E., Düll R., Wirth V., Werner W., Paulißen D. 1991. Zeigerwerte von Pflanzen in Mitteleuropa. Scripta Geobotanica 18: 1–248.
Evstigneev O.I., Gornov A.V. 2021. Reserve meadow: results of 30 years of monitoring. Russian Journal of Ecosystem Ecology 6(2). DOI: 10.21685/2500-0578-2021-2-2
Fick S.E., Hijmans R.J. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37(12): 4302–4315. DOI: 10.1002/joc.5086
Fielding A.H., Bell J.F. 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24(1): 38–49. DOI: 10.1017/S0376892997000088
Gao J., Wang W., Guo X., Zhu S., Chen Sh., Zhang R. 2014. Nutrient removal capability and growth characteristics of Iris sibirica in subsurface vertical flow constructed wetlands in winter. Ecological Engineering 70: 351–361. DOI: 10.1016/j.ecoleng.2014.06.006
Gatina E.L. 2015. To distribution of Iris sibirica L. in the territory of Perm region. Bulletin of Perm University. Biology 3: 203–206. [In Russian]
GBIF.org. 2024. GBIF Occurrence Download. Available from https://doi.org/10.15468/dl.4rxt2u
Grulich V. 2012. Red List of vascular plants of the Czech Republic: 3rd edition. Preslia 84(3): 631–645.
Guisan A., Petitpierre B., Broennimann O., Daehler C., Kueffer Ch. 2014. Unifying niche shift studies: Insights from biological invasions. Trends in Ecology and Evolution 29(5): 260–269. DOI: 10.1016/j.tree.2014.02.009
Guisan A., Thuiller W., Zimmermann N. 2017. Habitat Suitability and Distribution Models: With Applications in R. Cambridge: University Printing House. 462 p. DOI: 10.1017/9781139028271
Hijmans R.J. 2012. Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. Ecology 93(3): 679–688. DOI: 10.1890/11-0826.1
Hijmans R.J., Phillips S.J., Leathwick J., Elith J. 2017. dismo: Species Distribution Modeling. R package version 1.3-3. Available from https://CRAN.R-project.org/package=dismo
Hrivnák R., Slezák M., Dudáš M., Galvánek D., Labovská T., Miháliková T. 2024. Distribution of plant species Iris sibirica and its vegetation affinity in Slovakia. Biologia 79(9): 2649–2664. DOI: 10.1007/s11756-024-01719-0
Jain A.K. 2010. Data Clustering: 50 Years Beyond K-Means. Pattern Recognition Letters 31(8): 651–666. DOI: 10.1016/j.patrec.2009.09.011
Kassambara A., Mundt F. 2019. Factoextra: Extract and Visualize the Results of Multivariate Data Analyses. Available from https://rdrr.io/cran/factoextra/
Khela S. 2013. Iris sibirica (Europe assessment). In: The IUCN Red List of Threatened Species 2013: e.T203236A2762502. Available from https://www.iucnredlist.org/species/203236/2762502
Kostrakiewicz K. 2008. Population structure of a clonal endangered plant species Iris sibirica L. in different habitat conditions. Polish Journal of Ecology 56(4): 581–592.
Kostrakiewicz K. 2007. The effect of dominant species on numbers and age structure of Iris sibirica L. population on blue moor-grass meadow in Southern Poland. Acta Societatis Botanicorum Poloniae 76(2): 165–173. DOI: 10.5586/asbp.2007.020
Kostrakiewicz-Gierałt K., Podgórska M. 2020. Regeneration of the rare meadow species Iris sibirica in a postcultural land. Botany Letters 167(3): 331–339. DOI: 10.1080/23818107.2020.1784272
Kozyr M.S., Yakushenko D.M., Podorozhniy D.S. 2008. The ecological and coenotic characteristic of Iris sibirica L. in the flood-lands of Seim river. Introduktsiya Roslyn 4: 51–58. [In Ukrainian]
Kramer-Schadt S., Niedballa J., Pilgrim J.D., Schröder B., Lindenborn J., Reinfelder V., Stillfried M., Heckmann I., Scharf A.K., Augeri D.M., Cheyne S.M., Hearn A.J., Ross J., Macdonald D.W., Mathai J., Eaton J., Marshall A.J., Semiadi G., Rustam R., Bernard H., Alfred R., Samejima H., Duckworth J.W., Breitenmoser-Wuersten C., Belant J.L., Hofer H., Wilting A. 2013. The importance of correcting for sampling bias in MaxEnt species distribution models. Diversity and Distributions 19(11): 1366–1379. DOI: 10.1111/ddi.12096
Kryukova A.V., Mustafina A.N., Abramova L.M., Golovanov Y.M., Muldashev A.A. 2023. Morphology Features and Seed Productivity of Iris sibirica L. (Iridaceae Juss.) in the Trans-Urals of the Bashkortostan Republic. Vestnik Tomskogo Gosudarstvennogo Universiteta, Biologiya 64: 30–51. [In Russian]
Landolt E. 1977. Ökologische Zeigerwerte zur Schweizer Flora. Zürich: Geobotanischen Institutes der Eidg. Techn. Hochschule, Stiftung Rübel. 208 p.
Le S., Josse J., Husson F. 2008. FactoMineR: An R Package for Multivariate Analysis. Journal of Statistical Software 25(1): 1–18. DOI: 10.18637/jss.v025.i01
Levchenko L.S. 2022. Potential range change of the protected species Iris sibirica L. under the influence of projected climate change. In: A.M. Adam, N.I. Laptev, N.L. Yablochkina, N.N. Ilyinskikh, M.V. Olonova (Eds): Ecology and Environmental Management. Tomsk: Literaturnoe byuro. P. 48–50. [In Russian]
Lissovsky A.A., Dudov S.V. 2020. Advantages and limitations of application of the species distribution modeling methods. 2. Maxent. Zhurnal Obshchei Biologii 81(2): 135–146. DOI: 10.31857/S0044459620020049 [In Russian]
Litvinskaya S.A., Murtazaliev R.A. 2013. Flora of the North Caucasus. Moscow: Phyton XXI. 687 p. [In Russian]
Meusel H., Jäger E.J. 1992. Vergleichende Chorologie der Zentraleuropaischen Flora. Band III. Jena, Stuttgart, New York: Gustav Fischer Verlag. 333 p.
Mojsejchik E.V., Sozinov O.V. 2017. Species diversity of mineral island of the Zvanets Reserve. In: Biological Autumn of 2017 (To the science year in Belarus). Minsk: Belarusian State University. P. 197–199. [In Russian]
Mu-Za-Chin V.V., Shukal V.V. 2016. The characteristic of Iris sibirica L. (Iridaceae) coenopopulations in river floodplains in the Bryansk region. Bulletin of Bryansk dpt. of RBS 2(8): 36–43. [In Russian]
Ovchinnikova Yu.A., Shabalkina S.V. 2019. On ecological preferences of Iris sibirica L. In: T.Y. Ashihmina (Ed.): Ecology of the native land: problems and solutions. Kirov: Vyatka State University. P. 277–282. [In Russian]
Ovesnov S.A., Efimik E.G. 2014. Flora of the historico-natural complex «Spasskaya gora» (Perm region). Bulletin of Udmurt University. Series Biology. Earth Sciences 4: 18–26. [In Russian]
Peterson A.T. 2004. Predicting the geography of species' invasions via ecological niche modeling. Quarterly Review of Biology 78(4): 419–33. DOI: 10.1086/378926
Peterson A.T., Soberón J., Pearson R.G., Anderson R.P., Martínez-Meyer E., Nakamura M., Araújo M.B. 2011. Ecological Niches and Geographic Distributions (MPB-49). Princeton: Princeton University Press. 328 p. DOI: 10.1515/9781400840670
Petrova I.V., Sannikov S.N., Tembotova F.I., Sannikova N.S., Farzaliev V.S., Mollaeva M.Z., Egorov E.V. 2017. Genogeography of Pinus sylvestris L. Populations in the Greater Caucasus and Crimea. Russian Journal of Ecology 48(6): 524–531. DOI: 10.1134/S106741361706008X
Phillips S.J., Dudík M. 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31(2): 161–175. DOI: 10.1111/j.0906-7590.2008.5203.x
Phillips S.J., Anderson R.P., Schapire R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190(3–4): 231–259. DOI: 10.1016/j.ecolmodel.2005.03.026
Phillips S.J., Anderson R.P., Dudík M., Schapire R.E., Blair M.E. 2017. Opening the black box: an open-source release of Maxent. Ecography 40(7): 887–893. DOI: 10.1111/ecog.03049
Pirogov Yu.K. Inaturalist platform as a tool for studying species of the genus Iris L. modern ranges of Iris sibirica and Iris sanguinea based on iNaturalist data. In: V.V. Chub (Ed.): Iris-2022. Moscow: Moscow University Press. P. 96–100. [In Russian]
POWO. 2025. Plants of the World Online. Kew: Royal Botanic Gardens. Available from http://www.plantsoftheworldonline.org/
Qazi A.W., Saqib Z., Zaman-ul-Haq M. 2022. Trends in species distribution modelling in context of rare and endemic plants: a systematic review. Ecological Processes 11(1): 40. DOI: 10.1186/s13717-022-00384-y
R Core Team. 2025. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Available from https://www.R-project.org
Ramensky L.G., Tsatsenkin I.A., Chizhikov O.N., Antipin N.A. 1956. Ecological assessment of fodder lands by vegetation cover. Moscow: State Publishing House of Agricultural Literature. 471 p. [In Russian]
Red Data Book of the Republic of Crimea. Simferopol: IT ARIAL, 2015. 480 p. [In Russian]
Red Data Book of the Stavropolsky Krai. Stavropol: IP Andreev Igor Vladimirovich, 2013. 383 p. [In Russian]
Salamon-Albert É., Lőrincz P., Attila B. 2010. Iridetum sibiricae Philippi 1960 in Hungary. Acta Botanica Hungarica 52(1–2): 177–196. DOI: 10.1556/ABot.52.2010.1-2.e3
Schoener T.W. 1968. The Anolis Lizards of Bimini: Resource Partitioning in a Complex Fauna. Ecology 49(4): 704–726. DOI: 10.2307/1935534
Scrypec K.I., Tasenkevich L.O., Seniv M.M. 2020. Iris sibirica (Iridaceae) on the territory of Western Ukraine. Biosystems Diversity 28(3): 211–215. DOI: 10.15421/012027
Sillero N., Barbosa A.M. 2021. Common mistakes in ecological niche models. International Journal of Geographical Information Science 35(2): 213–226. DOI: 10.1080/13658816.2020.1798968
Sillero N., Arenas-Castro S., Enriquez-Urzelai U., Vale C.G., Sousa-Guedes D., Martínez-Freiría F., Real R., Barbosa A.M. 2021. Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling. Ecological Modelling 456: 109671. DOI: 10.1016/j.ecolmodel.2021.109671
Sillero N., Campos J., Arenas-Castro S., Barbosa A.M. 2023. A curated list of R packages for ecological niche modelling. Ecological Modelling 476: 110242. DOI: 10.1016/j.ecolmodel.2022.110242
Slepchenko N.A., Kozina V.V., Shoshina Ye.I. 2018. Iris sibirica in Russian humid subtropics. In: Problems of Botany of Southern Siberia and Mongolia. Barnaul: Barnaul State University. P. 513–515. [In Russian]
SRTM. 2025. Shuttle Radar Topography Mission. Available from https://srtm.csi.cgiar.org/
Straubinger C., Reisch C., Poschlod P. 2023. Effects of historical management on the vegetation and habitat properties of wet meadows in Germany. Restoration Ecology 31(5): e13839. DOI: 10.1111/rec.13839
Syfert M.M., Smith M.J., Coomes D.A. 2013. The effects of sampling bias and model complexity on the predictive performance of maxent species distribution models. PLoS ONE 8(2): e55158. DOI: 10.1371/journal.pone.0055158
Tichý L., Axmanová I., Dengler J., Guarino R., Jansen F., Midolo G., Nobis M.P., Van Meerbeek K., Aćić S., Attorre F., Bergmeier E., Biurrun I., Bonari G., Bruelheide H., Campos J.A., Čarni A., Chiarucci A., Ćuk M., Ćušterevska R., Didukh Ya., Dítě D., Dítě Z., Dziuba T., Fanelli G., Fernández-Pascual E., Garbolino E., Gavilán R.G., Gégout J.C., Graf U., Güler B. et al. 2023. Ellenberg-type indicator values for European vascular plant species. Journal of Vegetation Science 34(1): e13168. DOI: 10.1111/jvs.13168
Tsepkova N.L., Chadaeva V.A. 2019. Demographic indicators of Iris sibirica L. cenopopopulations under conditions of post-grazing demutation of mountain meadows in the territory of Protected Areas of the Western and Central Caucasus. In: Current issues of biodiversity conservation and ecologically balanced nature management in the Western Caucasus. Nalchik: Tembotov Institute of Ecology of Mountain Territories of RAS. P. 121–122. [In Russian]
Tzvelev N.N. 1979. Genus. 2. Iris L. In: Flora of European part of USSR. Vol. 4. Leningrad: Nauka. P. 299–307. [In Russian]
Vignali S., Lörcher F., Hegglin D., Arlettaz R., Braunisch V. 2021. Modelling the habitat selection of the bearded vulture to predict areas of potential conflict with wind energy development in the Swiss Alps. Global Ecology and Conservation 25: e01405. DOI: 10.1016/j.gecco.2020.e01405
Wang W.L., Gao J.Q., Guo X., Li W.C., Tian X.Y., Zhang R.Q. 2012. Long-term effects and performance of two-stage baffled surface flow constructed wetland treating polluted river. Ecological Engineering 49: 93–103. DOI: 10.1016/j.ecoleng.2012.08.016
Wang Y.S., Xie B.Y., Wan F.H., Xiao Q.M., Dai L.Y. 2008. Application of ecologic niche models in explanation of niche shift of invasive alien species. Acta Ecologica Sinica 28: 4974–4981.
Warren D.L., Glor R.E., Turelli M. 2008. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62(11): 2868–2883. DOI: 10.1111/j.1558-5646.2008.00482.x
Warren D.L., Glor R.E., Turelli M. 2010. ENMTools: A Toolbox for Comparative Studies of Environmental Niche Models. Ecography 33(3): 607–611. DOI: 10.1111/j.1600-0587.2009.06142.x
Webb D.A. 1980. Iris L. In: T.G. Tutin, V.H. Heywood (Eds.): Flora Europaea. Alismataceae to Orchidaceae. Vol. 5. Cambridge: Cambridge Univversity Press. P. 87–92.
Wickham H. 2009. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag. 213 p.
WorldClim2. 2025. WorldClim climate data base. Available from https://worldclim.com/version2
Yilmaz H., Yilmaz O.Y., Akyüz Y.F. 2017. Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model. Ecology and Evolution 7(4): 1112–1124. DOI: 10.1002/ece3.2766
Yutang Z., Noltie H.J., Mathew B. 2000. Iridaceae A. L. Jussieu. In: Z.Y. Wu, P.H. Raven (Eds.): Flora of China. Vol. 24. Beijing, St. Louis: Science Press, Missouri Botanical Garden Press. P. 297–313.