in

Prediction of habitat suitability for Patrinia sibirica Juss. in the Southern Urals

  • 1.

    Addison, P. F. et al. Practical solutions for making models indispensable in conservation decision-making. Divers. Distrib. 19, 490–502 (2013).

    Article 

    Google Scholar 

  • 2.

    Bosso, L. et al. Nature protection areas of Europe are insufficient to preserve the threatened beetle Rosalia alpina (Coleoptera: Cerambycidae): Evidence from species distribution models and conservation gap analysis. Ecol. Entomol. 43, 192–203 (2018).

    Article 

    Google Scholar 

  • 3.

    Lentini, P. et al. Using fossil records to inform reintroduction of the kakapo as a refugee species. Biol. Cons. 217, 157–165 (2018).

    Article 

    Google Scholar 

  • 4.

    Krasheninnikov, I. M. Analysis of the Southern Urals relict flora in connection with the Pleistocene vegetation history and paleogeography. Sovetskaya Bot. 4, 16–45 (1937) (in Russian).

    Google Scholar 

  • 5.

    Gorchakovsky, P. L. & Shurova, E.A. Rare and Endangered Plants of Urals and Cis-Urals 208–209 (Nauka, 1982) (in Russian).

  • 6.

    Gorchakovsky, P.L. The Plant World of the Ural High Mountains 283–285 (Nauka, 1975) (in Russian).

  • 7.

    Red Book of the Chelyabinsk Oblast: Animals, Plants, Fungi. 391 (ed A. V. Lagunov) (2017) (in Russian).

  • 8.

    Red Book of the Republic of Bashkortostan. Plants and Fungi 227 (ed B. M. Mirkin) (MediaPrint, 2011) (in Russian).

  • 9.

    Damschen, E. I. et al. Endemic plant communities on special soils: Early victims or hardy survivors of climate change?. J. Ecol. 100, 1122–1130 (2012).

    Article 

    Google Scholar 

  • 10.

    Spasojevic, M. J., Damschen, E. I. & Harrison, S. Patterns of seed dispersal syndromes on serpentine soils, examining the roles of habitat patchiness, soil infertility and correlated functional traits. Plant Ecol. Divers. 7, 401–410 (2014).

    Article 

    Google Scholar 

  • 11.

    Abdullina, L. A. Introduction of some rare medicinal plants in the Ufa Botanical Garden. In: Biodiversity of the Ural’s flora and adjacent territories: Proceedings of the All-Russian Conference with international participation. 319–320 (Goshchitskiy, 2012) (in Russian).

  • 12.

    Rossington, N., Yost, J. & Ritter, M. Water availability influences species distributions on serpentine soils. Madroño 65, 68–79 (2018).

    Article 

    Google Scholar 

  • 13.

    Byrne, M. et al. Persistence and stochasticity are key determinants of genetic diversity in plants associated with banded iron formation inselbergs. Biol. Rev. 94, 753–772 (2018).

    Article 

    Google Scholar 

  • 14.

    Corlett, R. T. & Tomlinson, K. W. Climate change and edaphic specialists: Irresistible force meets immovable object?. Trends Ecol. Evol. 35, 367–376 (2020).

    Article 

    Google Scholar 

  • 15.

    Khotinskii, N. A., Nemkova, V. K. & Surova, T. G. Main stages of Ural vegetation and climate development in Holocene. Archaeol. Issues Urals 16, 145–153 (1982) (in Russian).

    Google Scholar 

  • 16.

    Shiyatov, S. G. Experience in using old photographs for studying changes in forest vegetation at its upper limit. Floristic and Geobotanical Studies in the Urals 76–109 (1983) (in Russian).

  • 17.

    Moiseev, P. A., Shiyatov, S. G. & Grigor’yev, A. A. Climatogenic Dynamics of Woody Vegetation at the Upper Limit of Its Distribution on the Bolshoy Taganay Ridge over the Past Century 113–119 (ed V.A. Mukhin) (UrO RAS, 2016) (in Russian).

  • 18.

    Grigor’ev, A. A. et al. The advance of woody and shrub vegetation to the mountains and changes in the composition of tundra communities (Poperechnaya mountain, the Zigalga mountain range in the Southern Urals). J. Sib. Federal Univ. Biol. 11, 218–236 (2018) (in Russian).

    Article 

    Google Scholar 

  • 19.

    Brecka, A. F., Shahi, C. & Chen, H. Y. Climate change impacts on boreal forest timber supply. For. Policy Econ. 92, 11–21 (2018).

    Article 

    Google Scholar 

  • 20.

    Petchey, O. L. et al. The ecological forecast horizon, and examples of its uses and determinants. Ecol. Lett. 18, 597–611 (2015).

    Article 

    Google Scholar 

  • 21.

    Jarnevich, C. S. et al. Caveats for correlative species distribution modeling. Ecol. Inform. 29, 6–15 (2015).

    Article 

    Google Scholar 

  • 22.

    Global Biodiversity Information Facility (GBIF). Occurrence Download https://doi.org/10.15468/dl.fswlyt (2019).

  • 23.

    Knyazev, M. S. Rock flora of river valleys in the Urals. Botanicheskii Zhurnal 103, 695–726 (2018) (in Russian).

    Google Scholar 

  • 24.

    Karimova, O. A., Mustafina, A. N. & Golovanov, Y. Age structure of coenopopulations of Patrinia sibirica (Valerianaceae) in South Ural. Plant Resour. 52, 49–65 (2016) (in Russian).

    Google Scholar 

  • 25.

    Yates, K. L. et al. Outstanding challenges in the transferability of ecological models. Trends Ecol. Evol. 33, 790–802 (2018).

    Article 

    Google Scholar 

  • 26.

    Bamford, A. J. et al. Trade-offs between specificity and regional generality in habitat association models: A case study of two species of African vulture. J. Appl. Ecol. 46, 852–860 (2009).

    Article 

    Google Scholar 

  • 27.

    Telyatnikov, M. Y. Syntaxonomy of dryas tundra and kobresia cryophytic meadows of the East Sayan. Plant World Asian Russia 1, 48–63 (2014) (in Russian).

    Google Scholar 

  • 28.

    Zibzeyev, E. G. & Nedovesova, T. A. Syntaxa of Dryas tundra of West Sayan mountains. Turczaninowia 17, 38–59 (2014) (in Russian).

    Article 

    Google Scholar 

  • 29.

    Booth, T. H., Nix, H. A., Busby, J. R. & Hutchinson, M. F. Bioclim: The first species distribution modelling package, its early applications and relevance to most current MaxEnt studies. Divers. Distrib. 20, 1–9 (2014).

    Article 

    Google Scholar 

  • 30.

    Karger, D. N., Conrad, O. & Böhner, J. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 1–20 (2017).

    Article 

    Google Scholar 

  • 31.

    McSweeney, C. F. et al. Selecting CMIP5 GCMs for downscaling over multiple regions. Clim. Dyn. 44, 3237–3260 (2015).

    Article 

    Google Scholar 

  • 32.

    Sanderson, B. M., Knutti, R. & Caldwell, P. A representative democracy to reduce interdependency in a multimodel ensemble. J. Clim. 28, 5171–5194 (2015).

    ADS 
    Article 

    Google Scholar 

  • 33.

    Hof, A. R. & Allen, A. M. An uncertain future for the endemic Galliformes of the Caucasus. Sci. Total Environ. 651, 725–735 (2019).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 34.

    Gent, P. R. et al. The community climate system model version 4. J. Clim. 24, 4973–4991 (2011).

    ADS 
    Article 

    Google Scholar 

  • 35.

    Volodin, E. M., Dianskii, N. A. & Gusev, A. V. Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations. Izv. Atmos. Ocean. Phys. 46(4), 414–431. https://doi.org/10.1134/S000143381004002X (2010).

    Article 

    Google Scholar 

  • 36.

    Bentsen M. et al. The Norwegian Earth System Model NorESM1-M – Part 1: Description and basic evaluation of the physical climate. Geosci. Model Dev. 6(3), 687–720. https://doi.org/10.5194/gmd-6-687-2013 (2013).

    ADS 
    Article 

    Google Scholar 

  • 37.

    Watanabe S. et al. MIROC-ESM 2010: model description and basic results of CMIP5-20c3m experiments. Geosci. Model. Dev. Discuss. 4(4), 845–872. https://doi.org/10.5194/gmd-4-845-2011 (2011).

    ADS 
    Article 

    Google Scholar 

  • 38.

    Danielson, J. J., Gesch, D. B. Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010). Garretson: U.S. Geological Survey 26 (2011).

  • 39.

    Poggio, L. et al. SoilGrids 2.0: Producing soil information for the globe with quantified spatial uncertainty. Soil 7, 217–240 (2021).

    Article 

    Google Scholar 

  • 40.

    Phillips, S. J., Dudík, M. & Schapire, R. E. Maxent software for modeling species niches and distributions (Version 3.4.1). Available from url: http://biodiversityinformatics.amnh.org/open_source/maxent/ (2020).

  • 41.

    Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An open-source release of Maxent. Ecography 40, 887–893 (2017).

    Article 

    Google Scholar 

  • 42.

    Dormann, C. F. et al. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).

    Article 

    Google Scholar 

  • 43.

    Di Pasquale, G. et al. Coastal pine-oak glacial refugia in the Mediterranean basin: A biogeographic approach based on charcoal analysis and spatial modelling. Forests 11, 673 (2020).

    Article 

    Google Scholar 

  • 44.

    Swets, J. A. Measuring the accuracy of diagnostic systems. Science 240, 1285–1293 (1988).

    ADS 
    MathSciNet 
    CAS 
    Article 

    Google Scholar 

  • 45.

    Ahmed, N. et al. Species Distribution Modelling performance and its implication for Sentinel-2-based prediction of invasive Prosopis juliflora in lower Awash River basin, Ethiopia. Ecol. Process. 10, 1–16 (2021).

    Article 

    Google Scholar 


  • Source: Ecology - nature.com

    For campus “porosity hunters,” climate resilience is the goal

    New “risk triage” platform pinpoints compounding threats to US infrastructure