Implementing a new approach to effective conservation of genetic diversity, with ash (Fraxinus excelsior) in the UK as a case study

Gene conservation programs help safeguard species and tangibly benefit ecological restoration, agriculture, forestry, and horticulture. Here we describe a new method for deciding which and how many populations and individuals to conserve ex situ, and we demonstrate the method by evaluating collections of European Ash (Fraxinus excelsior) for an ongoing seed-banking project, the UK National Tree Seed Project (NTSP). The method uses simulations and geographic distribution data, and does not require (but can utilize) genetic data. We estimate that NTSP collections have captured >90% of all alleles and of locally common alleles. We identified optimal sampling solutions at large and small spatial scales, and for northern isolated vs. southern core populations. We also quantified genetic “points of diminishing returns” with a more precise method than previous studies. This analysis revealed that (for European ash, for a goal of capturing one copy of each allele) an optimal “stopping point” is approximately 35 populations, 10 to 30 trees per population, and 30 seeds per tree. Overall, we conclude that the NTSP protocol of random sampling of at least 15 trees per population from two populations per seed zone is effective. We demonstrated how collectors can adjust the number of populations, individuals and seeds sampled using the concept of “genetic equivalence”, allowing projects to accommodate practical or ecological constraints. Lastly we showed that for a conservation goal of 50 allele copies rather than one copy, a much larger sampling effort is needed (>150 populations). This new approach can be tailored to any species. It is applicable to any seed collection seeking to capture genetic diversity, as well as in situ gene conservation approaches. We emphasize that the ability to quantitatively estimate the outcome of gene conservation activities can help design, justify, or evaluate future programs.