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      A spatial stream-network approach assists in managing the remnant genetic diversity of riparian forests

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          Abstract

          Quantifying the genetic diversity of riparian trees is essential to understand their chances to survive hydroclimatic alterations and to maintain their role as foundation species modulating fluvial ecosystem processes. However, the application of suitable models that account for the specific dendritic structure of hydrographic networks is still incipient in the literature. We investigate the roles of ecological and spatial factors in driving the genetic diversity of Salix salviifolia, an Iberian endemic riparian tree, across the species latitudinal range. We applied spatial stream-network models that aptly integrate dendritic features (topology, directionality) to quantify the impacts of multiple scale factors in determining genetic diversity. Based on the drift hypothesis, we expect that genetic diversity accumulates downstream in riparian ecosystems, but life history traits (e.g. dispersal patterns) and abiotic or anthropogenic factors (e.g. drought events or hydrological alteration) might alter expected patterns. Hydrological factors explained the downstream accumulation of genetic diversity at the intermediate scale that was likely mediated by hydrochory. The models also suggested upstream gene flow within basins that likely occurred through anemophilous and entomophilous pollen and seed dispersal. Higher thermicity and summer drought were related to higher population inbreeding and individual homozygosity, respectively, suggesting that increased aridity might disrupt the connectivity and mating patterns among and within riparian populations.

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          Beyond Bonferroni: Less conservative analyses for conservation genetics

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            Characterising performance of environmental models

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              Calculations of population differentiation based on GST and D: forget GST but not all of statistics!

              G(ST)-values and its relatives (F(ST)) belong to the most used parameters to define genetic differences between populations. Originally, they were developed for allozymes with very low number of alleles. Using highly polymorphic microsatellite markers it was often puzzling that G(ST)-values were very low but statistically significant. In their papers, Jost (2008) and Hedrick (2005) explained that G(ST)-values do not show genetic differentiation, and Jost suggested calculating D-values instead. Theoretical mathematical considerations are often difficult to follow; therefore, we chose an applied approach comparing two artificial populations with different number of alleles at equal frequencies and known genetic divergence. Our results show that even for more than one allele per population G(ST)-values do not calculate population differentiation correctly; in contrast, D-values do reflect the genetic differentiation indicating that data based on G(ST)-values need to be re-evaluated. In our approach, statistical evaluations remained similar. We provide information about the impact of different sample sizes on D-values in relation to number of alleles and genetic divergence. © 2010 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                patri@isa.ulisboa.pt
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 May 2019
                1 May 2019
                2019
                : 9
                : 6741
                Affiliations
                [1 ]ISNI 0000 0001 2181 4263, GRID grid.9983.b, Centro de Estudos Florestais, Instituto Superior de Agronomia, , Universidade de Lisboa, Edifício Azevedo Gomes, Tapada da Ajuda, ; 1349-017 Lisboa, Portugal
                [2 ]ISNI 0000 0004 1936 8470, GRID grid.10025.36, Institute of Integrative Biology, Department of Evolution, Ecology, and Behaviour, , University of Liverpool, ; Crown Street, Liverpool, L69 7ZB United Kingdom
                [3 ]ISNI 0000 0001 1503 7226, GRID grid.5808.5, Plant Biology, CIBIO/InBio, Centro de Investigação em Biodiversidade e Recursos Genéticos, Laboratório Associado, , Universidade do Porto, Campus Agrário de Vairão, ; 4485-661 Vairão, Portugal
                [4 ]Ecofield, Monitorizações, Estudos e Projectos, LDA, Carcavelos, Portugal
                [5 ]ISNI 0000000121821287, GRID grid.12341.35, Centro de Investigação e Tecnologias Agroambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, Quinta de Prados, ; Apartado 1013, 5000-801 Vila Real, Portugal
                [6 ]ISNI 0000 0001 0190 2100, GRID grid.420943.8, INIAV - Instituto Nacional de Investigação Agrária e Veterinária, I.P., Unidade Estratégica de Biotecnologia e Recursos Genéticos, ; Lisboa, Portugal
                [7 ]ISNI 0000 0000 9310 6111, GRID grid.8389.a, LabOr- Laboratório de Ornitologia, ICAAM - Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, ; 7002-554 Évora, Portugal
                [8 ]ISNI 0000 0001 2181 4263, GRID grid.9983.b, Centre for Ecology, Evolution and Environmental Changes - cE3c, Faculdade de Ciências, Universidade de Lisboa, ; Lisboa, 1749-016 Portugal
                Author information
                http://orcid.org/0000-0001-8507-8429
                Article
                43132
                10.1038/s41598-019-43132-7
                6494995
                31043695
                a5d90793-14af-419e-a873-ec83d950ae7a
                © The Author(s) 2019

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 August 2018
                : 27 March 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001871, Ministry of Education and Science | Fundação para a Ciência e a Tecnologia (Portuguese Science and Technology Foundation);
                Award ID: UID/AGR/00239/2013
                Award ID: UID/AGR/04033/2019
                Award ID: UID/AGR/00239/2013
                Award ID: UID/AGR/00239/2013
                Award ID: UID/AGR/00239/2013
                Award Recipient :
                Funded by: EDP-Energias de Portugal, Fundo EDP para a Biodiversidade
                Funded by: EDP-Energias de Portugal, Fundo EDP para a Biodiversidade;
                Funded by: FundRef https://doi.org/10.13039/501100000780, European Commission (EC);
                Award ID: NTERREG-IVB-SUDOE–Ricover - SOE1/P2/P248
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                riparian ecology,population genetics,conservation biology,ecological modelling
                Uncategorized
                riparian ecology, population genetics, conservation biology, ecological modelling

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