Data from: Which species, how many, and from where: Integrating habitat suitability, population genomics, and abundance estimates into species reintroduction planning

Extirpated organisms are reintroduced into their former ranges worldwide
to combat species declines and biodiversity losses. The growing field of
reintroduction biology provides guiding principles for reestablishing
populations, though criticisms remain regarding limited integration of
initial planning, modeling frameworks, interdisciplinary collaborations,
and multi-species approaches. We used an interdisciplinary, multi-species,
quantitative framework to plan reintroductions of three fish species into
Abrams Creek, Great Smoky Mountains National Park, USA. We first assessed
the appropriateness of habitat at reintroduction sites for banded sculpin
(Cottus carolinae), greenside darter (Etheostoma blennioides), and mottled
sculpin (Cottus bairdii) using species distribution modeling. Next, we
evaluated the relative suitability of nine potential source stock sites
using population genomics, abundance estimates, and multiple-criteria
decision analysis (MCDA) based on known correlates of reintroduction
success. Species distribution modeling identified mottled sculpin as a
poor candidate, but banded sculpin and greenside darter as suitable
candidates for reintroduction based on species-habitat relationships and
habitats available in Abrams Creek. Genotyping by sequencing revealed
acceptable levels of genetic diversity at all candidate source stock
sites, identified population clusters, and allowed for estimating the
number of fish that should be included in translocations. Finally, MCDA
highlighted priorities among candidate source stock sites that were most
likely to yield successful reintroductions based on differential
weightings of habitat assessment, population genomics, and the number of
fish available for translocation. Our integrative approach represents a
unification of multiple recent advancements in the field of reintroduction
biology and highlights the benefit of shifting away from simply choosing
nearby populations for translocation to an information-based science with
strong a priori planning coupled with several suggested posteriori
monitoring objectives. Our framework can be applied to optimize
reintroduction successes for a multitude of organisms and advances the
science of reintroduction biology by simultaneously addressing a variety
of past criticisms of the field.