Transcription Audio

Hello and welcome. Today we’re diving into how genomics and wildlife health screening can actually change outcomes for species in Australia. Here’s the rule of thumb: the only good test is the one that changes what you do next. So we start with decisions, not technology. If a genomic profile or disease screen won’t alter a translocation, a breeding pair, or a biosecurity call, park it. Focus on evidence that bends the curve for the species you care about. Where do these tools deliver the most value? Three places: 1) High‑stakes decisions that are uncertain and hard to reverse—mixing isolated populations, releasing captive‑bred animals, moving fauna across bioregions. 2) Early baselines—genetic and disease—right at program inception. 3) Routine, risk‑based screening—preventative maintenance beats panicked testing after something goes wrong. And one non‑negotiable: every test must link to action. Before you order anything, ask: - What decision changes if the result is positive, negative, or inconclusive? - What’s the latest I could get that result and still act? - What are the costs of false positives and false negatives—to animals and people? - Is there a simpler tool that answers the question well enough? Let’s start with genomics. The tech sprinted ahead of budgets—and sometimes wisdom. The old belief that more markers are always better is gone. You need just enough resolution to change a management choice. We know genome‑wide variation matters for fitness and persistence. The classic 50/500 rule has shifted closer to 100/1000 to avoid inbreeding and maintain adaptive potential. But the value comes when you translate insights into who to move, who to pair, and when to intervene. Use genomics early to build a decision‑ready baseline—before captive breeding, translocations, or new populations. Quantify diversity, inbreeding, population structure, and connectivity so you can decide whether to mix populations, how many founders you need, and which sites supply or receive animals. A modest genome‑wide SNP panel across 20–50 individuals per population can reveal whether management units are distinct enough to warrant separate treatment. That matters under the EPBC Act when defining conservation units and planning recovery actions. Get the baseline early and you avoid expensive course corrections later. In captive programs, replace or augment pedigrees with genomic relatedness and mean‑kinship guidance. Pedigrees are often shallow or wrong. Genomic data corrects errors in a sizeable fraction of cases and improves pairings, reduces inbreeding, and retains more diversity. Runs of homozygosity give a direct read on individual inbreeding—more informative than paper pedigrees. Plan assisted gene flow using adaptive genomic signals—carefully. Genome‑environment associations can flag loci tied to climate tolerance or disease resistance. Treat these as supporting evidence alongside common‑garden trials, ecological data, and a cautious rollout. Use long‑read data and better assemblies sparingly, for species where structural variants likely matter. Resolve hybridisation, cryptic taxa, and legal designations with genome‑wide tools. When hybridisation threatens integrity—think dingoes and domestic dogs—or taxonomy is fuzzy, SNPs quantify introgression far better than a handful of markers. Decide in advance what thresholds trigger action, and align policy and communications so the science doesn’t outpace approvals. Now to health screening. The mindset is the same: start with risk and decisions, not a list of pathogens. Map the movement of animals, people, vehicles, feed, and gear. Identify high‑risk nodes—captive facilities, soft‑release sites, predator‑proof fences, wildlife hospitals, and livestock interfaces. Then design a risk‑based plan that fits those realities. Do early baselines. At program inception, establish a health profile for source populations and key sites. A focused panel—hematology, fecals, a few priority pathogens—can reveal endemic issues that will complicate future moves. Build routine screening around movement events: pre‑transfer, arrival, and post‑release checks. Quarantine with purpose and make duration proportional to incubation periods and test turnaround times. Write down the thresholds that will stop movement before you collect the first sample. Which tests? Use validated qPCR or PCR assays for high‑consequence pathogens. Serology helps with exposure history. Metagenomics or amplicon sequencing is powerful for outbreak investigation or when the agent is unknown—save it for special cases. For aquatic and cryptic species, environmental DNA can provide presence and sometimes pathogen signals if sensitivity allows. Don’t overlook necropsy and histopathology—they’re still among the best tools for discovering unexpected issues and improving live‑animal screening. Turnaround time matters. A perfect test is useless if the result lands after animals are on a truck. Build your schedule around the latest actionable time. If the cost of a false negative is high, use a two‑tier protocol: a rapid field screen followed by a confirmatory lab test. Account for test sensitivity and specificity in your decision tree. Logistics make or break screening. Standardize sample handling. Maintain the cold chain when needed, use consistent swabs, and train field teams to reduce variance. Pre‑label kits, pre‑load forms, and keep metadata tight: who, what, where, when, and why for every sample. Biosecurity is a team sport. Align movement permits, animal ethics, and site‑specific biosecurity plans with your screening protocol. Coordinate early with state regulators, agree on acceptable risk thresholds and release criteria, and build in a One Health perspective—consider zoonotic risks and occupational health for teams. Work with Traditional Owner ranger groups and Indigenous organisations from the outset. Co‑design sampling, agree on data governance and access, and respect Indigenous data sovereignty: who sees genomic and health data, how it’s used, and how benefits are shared. These relationships strengthen programs. Quality assurance is the unglamorous backbone. Use accredited labs, ask about validation, and join proficiency testing where available. Version‑control protocols, archive raw data securely, and, when appropriate, share anonymized datasets to benchmark over time. Let’s talk budgets. Spend where it changes a decision. A small, well‑designed SNP panel usually beats an expensive whole‑genome data dump you can’t analyze or act on. Pooled sequencing can cut costs for baseline estimates. Share assays and panels across agencies and NGOs. Invest early in sample banks—tissue, blood, feathers, scats—so you can revisit questions as tools evolve without resampling animals. Common pitfalls? Chasing marginal signals because they’re interesting rather than useful. Over‑collecting data without an action plan. Forgetting the action window for test results. Underestimating the time and cost to interpret complex results—often higher than lab costs. The real power emerges when you integrate field and lab data. Pair genomic metrics with demographic and movement data to see whether a translocation improved survival, reproduction, and diversity. Track health screening alongside post‑release monitoring so you can adjust biosecurity in real time. Here’s a quick checklist you can use tomorrow: 1) Define the decision and the latest actionable time. 2) Map risks and choose tests that match those risks, not curiosity. 3) Lock in genetic and health baselines at program start. 4) Write thresholds and a decision tree before sampling. 5) Choose the smallest validated tool that answers the question. 6) Nail logistics: sampling, cold chain, metadata, and turnaround time. 7) Plan communications with regulators, Traditional Owner partners, and stakeholders so results translate to action. 8) Measure outcomes and feed them back into the next decision. Do these, and genomics and health screening stop being shiny distractions and become force multipliers—tools that help you make better choices, reduce risk, and deliver measurable gains for Australia’s species. Thanks for listening—and here’s to putting the right data, at the right time, in service of the decisions that matter.