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      Endemics determine bioregionalization in the alpine zone of the Irano-Anatolian biodiversity hotspot (South-West Asia)

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          Abstract

          Alpine habitats are characterized by a high rate of range restricted species compared to those of lower elevations. This is also the case for the Irano-Anatolian global biodiversity hotspot in South-West Asia, which is a mountainous area harbouring a high amount of endemic species. Using two quantitative approaches, Endemicity Analysis and Network-Clustering, we want to identify areas of concordant species distribution patterns in the alpine zone of this region as well as to test the hypothesis that, given the high proportion of endemics among alpine species, delimitation of these areas is determined mainly by endemic alpine species, i.e., areas of concordant species distribution patterns are congruent with areas of endemism. Endemicity Analysis identified six areas of concordant species distribution patterns irrespective of dataset (total alpine species versus endemic alpine species), whereas the Network-Clustering approach identified five and four Bioregions from total alpine species and endemic alpine species, respectively. Most of these areas have been previously identified using the endemic flora of different elevational zones. The identified units using both methods and both datasets are strongly congruent, proposing that they reveal meaningful distribution patterns. Bioregionalization in the Irano-Anatolian biodiversity hotspot appears to be strongly influenced by the endemic alpine species, a pattern likely to hold in alpine regions outside the Irano-Anatolian hotspot.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00035-021-00266-7.

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          Biodiversity hotspots for conservation priorities.

          Conservationists are far from able to assist all species under threat, if only for lack of funding. This places a premium on priorities: how can we support the most species at the least cost? One way is to identify 'biodiversity hotspots' where exceptional concentrations of endemic species are undergoing exceptional loss of habitat. As many as 44% of all species of vascular plants and 35% of all species in four vertebrate groups are confined to 25 hotspots comprising only 1.4% of the land surface of the Earth. This opens the way for a 'silver bullet' strategy on the part of conservation planners, focusing on these hotspots in proportion to their share of the world's species at risk.
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            Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
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              Climate change. Accelerating extinction risk from climate change.

              Mark Urban (2015)
              Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change-induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions.
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                Author and article information

                Contributors
                jalil.noroozi@univie.ac.at
                Journal
                Alp Bot
                Alp Bot
                Alpine Botany
                Springer International Publishing (Cham )
                1664-2201
                1664-221X
                4 August 2021
                4 August 2021
                2021
                : 131
                : 2
                : 177-186
                Affiliations
                [1 ]GRID grid.10420.37, ISNI 0000 0001 2286 1424, Department of Botany and Biodiversity Research, , University of Vienna, ; Vienna, Austria
                [2 ]GRID grid.411807.b, ISNI 0000 0000 9828 9578, Department of Biology, , Bu-Ali Sina University, ; Hamedan, Iran
                [3 ]GRID grid.412266.5, ISNI 0000 0001 1781 3962, Department of Plant Biology, Faculty of Biological Sciences, , Tarbiat Modares University, ; Tehran, Iran
                [4 ]GRID grid.14442.37, ISNI 0000 0001 2342 7339, Department of Pharmaceutical Botany, Faculty of Pharmacy, , Hacettepe University, ; Ankara, Turkey
                [5 ]GRID grid.411301.6, ISNI 0000 0001 0666 1211, Department of Geography, , Ferdowsi University of Mashhad, ; Mashhad, Iran
                [6 ]GRID grid.425585.b, ISNI 0000 0001 2259 6528, Natural History Museum of Vienna, ; Vienna, Austria
                [7 ]GRID grid.411301.6, ISNI 0000 0001 0666 1211, Geographic Information Science/System and Remote Sensing Laboratory (GISSRS: lab), , Ferdowsi University of Mashhad, ; Mashhad, Iran
                Author information
                http://orcid.org/0000-0003-4124-2359
                http://orcid.org/0000-0002-1782-6672
                http://orcid.org/0000-0001-5096-4818
                http://orcid.org/0000-0001-6934-1434
                http://orcid.org/0000-0002-5972-5191
                http://orcid.org/0000-0001-6233-416X
                http://orcid.org/0000-0002-8977-1754
                http://orcid.org/0000-0003-2811-3317
                Article
                266
                10.1007/s00035-021-00266-7
                8549998
                34721248
                0c8483d4-6a90-43a2-beca-1ba862ee5f18
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 4 May 2021
                : 22 July 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: P31898
                Award ID: 28489
                Award Recipient :
                Funded by: University of Vienna
                Categories
                Original Article
                Custom metadata
                © Swiss Botanical Society 2021

                alpine habitats,areas of endemism,bioregions,endemicity analysis,global biodiversity hotspots,network-clustering

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