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Genetic diversity and structure of Eusideroxylon zwageri (Teijsm. & Binn.) in Indonesia revealed by nuclear microsatellite markers

  • Sukartiningsih Sukartiningsih*
  • , Ida Luh Gede Nurtjahjaningsih
  • , Purnamila Sulistyawati
  • , Yohannes Wibisono
  • , Sumardi Sumardi
  • , Rina Laksmi Hendrati
  • , Liliana Baskorowati
  • , A. Y.P.B.C. Widyatmoko
  • , Istiana Prihatini
  • , Mashudi Mashudi
  • , Yayan Hadiyan
  • , Dedi Setiadi
  • , Sugeng Pudjiono
  • , Tisha Melia
  • , Hiroyuki Kurokochi
  • , Yoko Saito
  • , Yuji Ide
  • *Corresponding author for this work
  • Faculty of Forestry
  • Mulawarman University
  • Research Center for Applied Botany
  • National Research and Innovation Agency Republic of Indonesia
  • Research Center for Ecology and Ethnobiology
  • Department of Computer Science
  • Riau University
  • Department of Ecosystem Studies
  • The University of Tokyo

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Eusideroxylon zwageri (Teijsm. & Binn.) or ironwood, a durable and long-lived timber species native to Indonesia, is classified as vulnerable due to overexploitation and habitat fragmentation. This study evaluated genetic diversity and population structure of ironwood across nine populations in Kalimantan (Gunung Palung, Kapuas Hulu, Bukit Suharto, Kutai, Kintap, Berau, Busang) and Sumatra (Jambi, Musi Rawas) using 11 nuclear microsatellite markers. The results indicated moderate genetic diversity (HO: 0.511–0.623). Most Kalimantan populations exhibited significant heterozygosity deficiencies, as reflected by positive inbreeding coefficient (FIS) values (FIS: 0.091–0.224); in contrast, Sumatra populations showed no significant deviations (FIS: 0.055–171). Population genetic analyses revealed a significant bottleneck in all studied populations according to the Infinite Allele Model (IAM), while no significant bottleneck was detected under the Stepwise Mutation Model (SMM), Two-Phase Model (TPM), and model shift analysis. A dendrogram analysis, Principal Coordinate Analysis (PCoA), and STRUCTURE analysis grouped the populations into three distinct clusters, revealing regional genetic structuring. Analysis of Molecular Variance (AMOVA) demonstrated significant genetic differentiation among regions (15%, p < 0.001). The Approximate Bayesian Computation (ABC) analysis definitively identifies the hierarchical simple split model as the more biologically probable representation of ironwood’s evolutionary history compared to the traditional invasion model. This study concluded that ironwood populations in Indonesia exhibit moderate genetic diversity and are grouped into western Kalimantan, eastern Kalimantan, and Musi Rawas. Eastern Kalimantan, with its higher genetic richness and broader distribution, serves as a key gene pool for the species. Future research should focus on understanding ironwood’s adaptability to climate change and the role of gene flow in maintaining genetic diversity, particularly for the vulnerable Musi Rawas population.

Original languageEnglish
Pages (from-to)265-279
Number of pages15
JournalForest Science and Technology
Volume21
Issue number3
DOIs
Publication statusPublished - 2025
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Allelic richness
  • Kalimantan
  • Sumatera
  • ironwood
  • nSSRs
  • natural populations

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