Many threatened species only persist as small and isolated populations where mutually reinforcing genetic and demographic threats increase the risk of extinction. The successful conservation of species distributed across fragmented habitats might require, in addition to the protection and restoration of habitats, the deliberate displacement (translocation) of individuals from genetically differentiated populations to increase the genetic diversity and fitness of target populations, a process known as ‘genetic rescue’. However, designing genetic-rescue interventions (determining optimal size, frequency, and source of translocated populations) to maximise success is inherently uncertain. We report a new simulation study using a recently developed theoretical model (Beaman et al. Evol App 18, 2025) that replicates the mutually reinforcing interaction between demographic and genetic effects that increase extinction probability in small populations. We simulated a set of translocation scenarios that confront decision makers during the implementation of genetic rescue, including abundance and effective population size of source and target populations, number of individuals translocated and how frequently, population genetic metrics of diversity and differentiation, and the demographic composition (age-structure, sex-ratio) of the translocated cohort. We report the relative importance of these genetic-rescue variables based on their effects on reducing extinction risk and increasing the mean time to extinction for focal populations. We also highlight the potential for forward-projection simulations to increase the cost-effectiveness of conservation interventions and contribute to systematic conservation planning, evaluation, and monitoring.

Tracking population trends of threatened species is critical for conservation assessments, recovery planning, and biodiversity indices. However, threatened species data is often sparse, inconsistently sampled, and involves multiple sampling methods. Common approaches such as the chain method and generalised additive models that underpin biodiversity frameworks often fail or produce spurious trends when sites are unevenly sampled or lack temporal overlap.
To improve tracking and reporting of threatened species by the Queensland Threatened Species Unit, we developed a species-agnostic Bayesian state-space framework integrating disparate monitoring datasets while overcoming these limitations. In the framework, effort-scaled observations are modelled using zero-inflated lognormal likelihood, where zero-inflation probability is estimated hierarchically at the site level and automatically collapses to standard lognormal when zeros comprise less than 15%. It employs three-level nested random effects (location > site > sampling unit) that activate conditionally based on data structure, to allow model complexity to scale when required. The model uses a ‘time-aware’ first-order random walk with drift for the latent log-abundance to accommodate irregular sampling intervals and data gaps. The framework was implemented in NIMBLE with adaptive MCMC tuning and comprehensive convergence diagnostics.
This state-space modelling approach was applied to ten threatened Queensland vertebrates using Threatened Species Index and Threatened Species Operations data. Species datasets spanned diverse taxa, sampling methods, and spatiotemporal representation. Posterior predictive checks revealed good model fit across species, with diagnostics summarised into trajectory plot indices for public reporting. The framework successfully avoided artificial population spikes from site changes or uneven sampling effort, while credible intervals widened appropriately during data gaps, highlighting genuine uncertainty rather than false precision. This state-space modelling framework demonstrates improved population trajectory tracking with unified methodology, providing robust foundations for conservation assessments and biodiversity indices.

As global biodiversity rapidly plummets, it is important to consider holistic methods for understanding and reversing such declines. The Green Status of Ecosystems (GSE) is an emerging framework for measuring and assessing the recovery of entire ecosystem types. We sought to test the GSE method via a case study of the Australian Alpine Sphagnum Bog and Associated Fen ecosystem. We used expert input alongside historical and current data to assess the integrity of alpine peatlands across their distribution, generating an Ecosystem Recovery Category to reflect their present state. We used structured expert elicitation to understand the recovery status of this ecosystem across a range of conservation scenarios in the past, present and future. From these scenarios, we calculated five Conservation Impact Metrics to measure the importance of conservation in influencing the integrity of alpine peatlands, and their potential for short- and long-term recovery. The outputs from a GSE assessment provide easily communicable insights into the overall state of alpine peatlands that can be used to incentivise and inform conservation management, monitoring designs, and policy reporting. Formally measuring the state of ecosystem recovery using a standardised approach is essential for progressing towards the Global Biodiversity Framework’s targets and goals.

The Bininj/Mungguy have lived in Kakadu for over 65,000 years and hold deep knowledge of the region’s biodiversity. Kakadu National Park is recognised as a World Heritage site because of its cultural and natural values. Much of the publicly accessible information on Kakadu’s natural values is based on Balanda (non-Indigenous) research.
This presentation shares our journey so far, to centre Bininj/Mungguy leadership in a biodiversity project focused on orchids and fungi. Through a co-designed and Indigenous-led approach, the project has navigated complex pathways, involving permits, ethics approvals, Free Prior and Informed Consent, Indigenous Cultural Intellectual Property (ICIP), project Intellectual Property (IP), and Indigenous Data Sovereignty. We will reflect on how the project has grown beyond its original scientific scope, shaped by on-Country guidance and community priorities. This is not just a study of plants and fungi, it is a story about relationships, respect, reciprocity, and restoring authority to Traditional Owners in biodiversity research.
By sharing our experiences, we aim to support others to shift the research landscape toward approaches that are genuinely collaborative, ethical, and grounded in Indigenous governance.