Data from: Combining spatial, genetic, and environmental risk data to define and prioritize in situ conservation units

In situ management aims to preserve species and their genetic integrity
within their natural habitat. To achieve this, conservation strategies
must strike a balance between safeguarding genetic diversity, mitigating
environmental risks, and addressing practical management constraints.
Here, we present a clear and reproducible framework that addresses these
goals. We applied this framework to the Nightcap reserves in the Gondwanan
Rainforests of Australia, a UNESCO World Heritage site impacted by the
2019/20 Black Summer fires. We analysed the genetic diversity of 12
rainforest tree species, including three endangered species—Eidothea
hardeniana, Uromyrtus australis, and Elaeocarpus sedentarius—and examined
how fire risk, influenced by the presence of fire-dependent species such
as eucalypts, impacts genetic diversity. To guide specific in situ
management for the endangered species, we developed a flexible framework
that uses clustering algorithms (DBSCAN and k-means) to define spatial
management units while considering resource limitations (e.g., maximum
perimeter or area). Our framework also incorporates a composite genetic
value metric (combining Essential Biodiversity Variables heterozygosity,
allelic richness, and genetic differentiation) and evaluates future fire
risk based on vegetation flammability. This approach allowed us to
identify priority management areas while adhering to resource constraints.
We provide some reproducible examples of how the proposed framework can be
applied, either partially or fully, to optimize in situ conservation
efforts. Its flexibility allows for adjustments to fit different habitat
types, species, and environmental threats, making it a valuable tool for
enhancing conservation management across diverse conservation contexts.