Sample Planning Optimization Tool for conservation and population Genetics (SPOTG): a software for choosing the appropriate number of markers and samples

Sean Hoban, Oscar Gaggiotti, Giorgio Bertorelle, Pim Arntzen, Josef Bryja, Margarida Fernandes, Katie Frith, Peter Galbusera, Jose A. Godoy, Heidi C. Hauffe, Russel Hoelzel, Richard Nichols, Silvia Perez-Espona, Craig Primmer, Isa-Rita M. Russo, Gernot Segelbacher, Hans R. Siegismund, Marjatta Sihvonen, Per Sjoegren-Gulve, Cristiano VernesiCarles Vila, Michael W. Bruford, ConGRESS Consortium

Research output: Contribution to journalArticlepeer-review


Genetic data are frequently used to make inferences about evolutionary and ecological processes, but the choice of the number of genetic markers and samples for such studies is usually ad hoc. Unfortunately, suboptimal sampling routinely leads to ambiguous results. spotg is a user-friendly software for optimizing sampling strategy for five common genetic study topics: hybridization, temporal sampling, bottlenecks, connectivity and assignment. spotg facilitates formal evaluation of the expected statistical power of proposed sampling strategies before project implementation, by using stochastic genetic simulations of realistic population scenarios and various sampling schemes. We demonstrate use of the tool with two example species (lynx and bison) in which demographic history differs; the appropriate sampling strategy for detecting a genetic bottleneck differs dramatically between the two cases, with important implications for sample planning. spotg has an interactive graphical tool for exploring results, and extensive documentation, tips and tutorials to enable use by conservation managers, ecologists beginning to use genetics and students.

Original languageEnglish
Pages (from-to)299-303
Number of pages5
JournalMethods in ecology and evolution
Issue number3
Publication statusPublished - 27 Dec 2012


  • data analysis
  • statistical power
  • conservation interventions
  • monitoring
  • simulation
  • molecular ecology
  • management
  • LOCI

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