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<p>This study presents SST (Species Selection Tool), a climate-based framework designed to support species selection across geographic regions and climate scenarios. The tool was developed to enable breeders to examine species selection scenarios across countries and climate horizons. Beyond identifying promising species for testing, SST prioritizes candidate species, highlights opportunities for germplasm exchange, anticipates climate-driven shifts, and maps environmental clusters and adapted genetic resources to guide near- and long-term breeding strategies. Built with the Shiny framework in R, SST allows users to upload tabular data in CSV format for flexible analyses. We demonstrate its application for a <i>Eucalyptus</i> breeding example in Brazil, using occurrence data from GBIF and environmental covariates from TerraClimate and CHIRPS, and complemented by CMIP6 future climate projections. Temperature and precipitation data were used to compute 19 bioclimatic variables (BIO1–BIO19) for macroenvironmental classification and species suitability assessment. SST integrates five analytical indices, scaled from 0 to 1, producing an overall suitability index and ranking species accordingly. The tool identified <i>E. urophylla</i>, <i>E. brassiana</i>, <i>E. deglupta</i>, and <i>E. pellita</i> as the most suitable for the study area in the Maranhão State, Brazil. Open-source and user-friendly, SST accelerates breeding decisions, supports climate-adaptive planning, and provides access to advanced analytical tools. The tool is a useful contribution to forest management and forest tree breeding, supporting data-driven strategies for sustainable forestry under changing climates.</p>

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A new environmental-based tool to support forest breeders in selecting species adapted to current and near-term climate conditions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月15日

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  • Ricardo Cavalheiro,
  • Aurelio Mendes Aguiar,
  • Ranga Raju Vatsavai,
  • Mragisha Jain,
  • William M. Hammond,
  • Gary Hodge,
  • Juan Jose Acosta,
  • Roberto Fritsche-Neto

摘要

This study presents SST (Species Selection Tool), a climate-based framework designed to support species selection across geographic regions and climate scenarios. The tool was developed to enable breeders to examine species selection scenarios across countries and climate horizons. Beyond identifying promising species for testing, SST prioritizes candidate species, highlights opportunities for germplasm exchange, anticipates climate-driven shifts, and maps environmental clusters and adapted genetic resources to guide near- and long-term breeding strategies. Built with the Shiny framework in R, SST allows users to upload tabular data in CSV format for flexible analyses. We demonstrate its application for a Eucalyptus breeding example in Brazil, using occurrence data from GBIF and environmental covariates from TerraClimate and CHIRPS, and complemented by CMIP6 future climate projections. Temperature and precipitation data were used to compute 19 bioclimatic variables (BIO1–BIO19) for macroenvironmental classification and species suitability assessment. SST integrates five analytical indices, scaled from 0 to 1, producing an overall suitability index and ranking species accordingly. The tool identified E. urophylla, E. brassiana, E. deglupta, and E. pellita as the most suitable for the study area in the Maranhão State, Brazil. Open-source and user-friendly, SST accelerates breeding decisions, supports climate-adaptive planning, and provides access to advanced analytical tools. The tool is a useful contribution to forest management and forest tree breeding, supporting data-driven strategies for sustainable forestry under changing climates.