14
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Generalizations of genetic conservation principles in islands are not always likely: a case study from a Neotropical insular cactus

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Cereus insularis (Cereeae, Cactaceae) is an insular endemic and dominant element of the vegetation of Fernando de Noronha Islands (FNI), a Neotropical archipelago 350 km from mainland Brazil. Here, we estimate the levels of genetic diversity for C. insularis and investigate its genetic relationship with the closely allied C. fernambucensis, which is widespread along the Brazilian coast. We genotyped and analysed 112 individuals for ten nuclear microsatellite markers to understand genetic connectivity between insular and mainland populations. The levels of genetic diversity for this species indicate an absence of genetic erosion. Furthermore, the expected heterozygosity in C. insularis is consistent with a long-term colonization process of FNI. We identify signatures of recent and bilateral gene flow among mainland and insular populations. We explain our results taking into consideration the biogeographic hypothesis to explain the peripatric origin of C. insularis. Overall, this is a case study suggesting that the generalizations of genetic conservation principles in oceanic islands, such as low levels of genetic diversity, are not always the case. Rather than challenge these principles, we stress that island dynamism throughout time should be an important factor in explaining levels of genetic diversity in insular species.

          Related collections

          Most cited references93

          • Record: found
          • Abstract: not found
          • Article: not found

          WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Inference of Population Structure Using Multilocus Genotype Data

            We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Detecting the number of clusters of individuals using the software structure: a simulation study

              The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Botanical Journal of the Linnean Society
                Oxford University Press (OUP)
                0024-4074
                1095-8339
                May 01 2022
                April 13 2022
                December 18 2021
                May 01 2022
                April 13 2022
                December 18 2021
                : 199
                : 1
                : 210-227
                Affiliations
                [1 ]Departamento de Biologia, Universidade Federal de São Carlos (UFSCar), Sorocaba, Brazil
                [2 ]Departamento de Genética, Evolução, Microbiologia e Imunologia, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
                [3 ]Institute for Biology and Environmental Sciences, Carl von Ossietzky-University Oldenburg, Carl von Ossietzky-Strasse 9-11, 26111 Oldenburg, Germany
                [4 ]Departamento de Ecologia e Biologia Evolutiva, Universidade Federal de São Paulo (UNIFESP), Diadema, SP, Brazil
                [5 ]Programa de Pós-Graduação em Biologia Comparada, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo (USP), Ribeirão Preto, Brazil
                [6 ]Programa de Pós-Graduação em Botânica, Instituto de Ciências Biológicas, Universidade de Brasília (UNB), PO Box 04457, Brasília, DF, 70910970, Brazil
                [7 ]University of Gibraltar, Gibraltar Botanic Gardens Campus, The Alameda, PO Box 843, GX11 1AA, Gibraltar
                Article
                10.1093/botlinnean/boab076
                43c45841-7b04-4140-b76d-13d4118b6a23
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

                History

                Comments

                Comment on this article