Forensic Genomics and Spatial Intelligence of the Illicit Parrot Trade

Global wildlife trafficking is a multibillion-dollar criminal enterprise that threatens biodiversity worldwide. Parrots are by far the most heavily traded avian group listed under CITES. Our comprehensive evaluations have revealed that one-third of the world’s ~400 parrot species are threatened with extinction, declining faster than almost any comparable bird group due to the combined pressures of habitat loss and unsustainable trade (Olah et al. 2016, Biodiversity and Conservation). To combat this crisis, our research bridges forensic genomics, wildlife disease surveillance, spatial network modelling, and criminology to map, trace, and disrupt illegal trade routes from forest sourcing grounds to urban markets.

Under our current research framework, we apply cutting-edge genomic tools, disease diagnostic screening, and spatial intelligence across both primary hubs of global parrot trade:

  • Mexico: Integrating three decades of confiscation data, our recent study (Olah et al. 2026, PNAS) combined landscape ecology and criminological frameworks to study the Mexican parrot trade. We developed a secure, interactive mapping tool for proactive law enforcement. Alongside spatial modelling, we are deploying forensic genomic pipelines and health screening to trace the exact origin of confiscated birds and evaluate disease risks associated with illicit transport.
  • Indonesia: Concurrently in Southeast Asia—the global epicenter of wildlife trafficking—our work targets Indonesia, which was flagged as the highest priority country for parrot conservation due to high species diversity, endemicity, and severe poaching pressures (Olah et al. 2018, Emu). We previously demonstrated that the negative impacts of wildlife trade are already measurable in wild parrot populations on biodiverse Indonesian islands (Nandika et al. 2021, Diversity). Furthermore, by applying a criminological model to Indonesian market and seizure data, we revealed that both demand-driven factors and opportunity-driven factors significantly predict trade variation across species (Pires et al. 2021, Biological Conservation). Building on these insights, we are developing field-deployable genomic techniques and pathogen surveillance pipelines to assess population connectivity, assign provenance to seized birds, screen for wildlife diseases, and support prosecution against illegal poaching networks.

All project updates, interactive law enforcement portals, and media tools are centralised at our public platform: StopParrotTrade.org

This project is funded by the Australian Research Council, under a Discovery Early Career Researcher Award (DECRA project DE230100085), and hosted by the Fenner School of Environment and Society, The Australian National University (ANU). Our Indonesian collaborators are Prof. Dewi Prawiradilaga (BRIN) and the Konservasi Kakatua Indonesia. My international collaborators for this research include the Indonesian Parrot Project, Prof. Sam Banks (Charles Darwin University), Prof. Denise Syndercombe Court (King’s College London), Dr. Stephen Pires (Florida International University), and Prof. Rob Heinsohn (ANU).

Remote Sensing and Landscape Genetics

In a collaboration with spatial ecologist Prof. Greg Asner (Global Airborne Observatory) and Dr. Anabel Smith (University of Queensland), we combined remotely sensed canopy data with population genetic information on Red-and-green Macaws. Our publication (Olah et al. 2017, Landscape Ecology) established baseline landscape genetic information on natural dispersal barriers, assisting our understanding of how rapid anthropogenic change influences macaw population structure across the Amazon Basin.

Building on this collaboration with Dr. Asner and the Center for Global Discovery and Conservation Science (Arizona State University), we linked high-resolution forest canopy functional diversity maps across Peru to the traits, life histories, threat exposures, and evolutionary lineages of over 1,300 forest-dependent bird species. Our findings (Olah et al. 2026, Nature Communications) demonstrate that remotely sensed canopy functional composition—representing a forest’s unique chemical and structural fingerprint—acts as a strong, independent predictor of avian community structure. This work provides a scalable, data-driven framework to refine conservation gap analyses and prioritise protection across tropical resource landscapes.

In a separate international collaboration with biogeographer Dr. Javier Nori and his team at the Centro de Zoología Aplicada (Universidad Nacional de Córdoba) and the Instituto de Diversidad y Ecología Animal (CONICET-UNC) in Argentina, we evaluated the current and projected impacts of forest destruction on the conservation status of parrots globally (Vergara-Tabares et al. 2020, Global Change Biology). Our results highlighted that the existing spatial configuration and extent of protected area networks remain insufficient to safeguard the majority of these threatened species.

Ancient Feather DNA Study

In collaboration with anthropologist Prof. Izumi Shimada (Southern Illinois University, USA), Dr. Pere Bover (Universidad de Zaragoza, Spain), and Dr. Bastien Llamas (Australian Centre for Ancient DNA, University of Adelaide, Australia), we investigated 1,000-year-old parrot feathers excavated from an unlooted elite tomb at the coastal religious centre of Pachacamac, Peru. As tropical parrots do not occur naturally in this hyper-arid desert environment, we used a multi-proxy bioarchaeological approach—combining ancient DNA (aDNA) sequencing, stable isotope analysis, and computational landscape resistance modelling—to trace their origins and provenance.

Our findings, published in Nature Communications (2026), revealed that pre-Inca societies (the Ychsma and possibly Chimú) undertook the extraordinary logistical feat of transporting live Amazonian parrots over 500 km across the Andes. High genetic diversity in mitochondrial DNA proved these birds were sourced from wild rainforest populations rather than closed captive breeding facilities. Furthermore, stable isotope chemistry showed a diet of coastal maize fertilised by seabird guano, proving the birds were kept alive on the coast to provide a renewable harvest of sacred ritual plumage. Read our post on this research here.

Difficult Bird Research Group

The Difficult Bird Research Group (DBRG), led by Prof. Robert Heinsohn and Dr. Dejan Stojanovic, studies Australia’s most endangered birds and is dedicated to understanding their ecology and conservation. Their research focuses on understanding the processes that threaten endangered birds, and identifying the ways to prevent extinction. The ‘difficult birds’ are all extremely endangered, hard to find, occur in wild and rugged terrain, and move around the landscape.

As a Postdoctoral Research Fellow at the Fenner School of Environment & Society, ANU, I led the genetic analysis of hundreds of samples accumulated by the DBRG from the Critically Endangered Swift Parrot (Lathamus discolor) in Tasmania. The results provided vital genomic insights directly applicable to field management and species conservation. Through this research, we presented genetic evidence confirming the severe extinction risk of this species (Stojanovic et al. 2018, Animal Conservation); showed how sex ratio bias and shared paternity reduce their population viability (Heinsohn et al. 2019, Journal of Animal Ecology); published techniques to estimate the effective population size in endangered species (Olah et al. 2021, Animal Conservation); and evaluated how molecular marker selection (microsatellites vs. SNPs) influences these estimations to guide conservation practice (Olah et al. 2024, Ecology and Evolution).

Supported by the prestigious Endeavour Postdoctoral Research Award, I investigated spatio-temporal genetic changes and population size dynamics over a 100-year time frame in the Critically Endangered Regent Honeyeater (Anthochaera phrygia). By pairing field samples with historic museum collections from around the world, we analyzed the magnitude of historic genetic diversity lost in this species. In close collaboration with the Banks, Peakall, and Moritz labs, I adjusted the existing genomics protocols to work with both ancient (aDNA) and modern DNA samples. I eventually applied next-generation sequencing (NGS) technology: a hybridization RAD technique that included ddRAD library preparation of the probes from contemporary samples, in order to hybridize with fragmented aDNA successfully extracted from museum specimens (Olah et al. 2018, Protocols.io). Our results showed that the population structure in regent honeyeaters was historically low, which remains the case despite a severe fragmentation of the breeding range (Crates et al. 2019, PLOS ONE).

Ecology and Population Genetics of Two Large Macaw Species in the Peruvian Amazon

My PhD project was completed at The Australian National University (ANU) through a prestigious international scholarship (IPRS) from the ANU and an Endeavour Scholarship from the Department of Education of the Australian Government. My research focused on the ecology and conservation of wild macaw populations in the Peruvian Amazon. As part of this research I gained extensive experience in the nesting ecology of wild parrots and in genetics. As presented in a series of my publications, I developed and validated non-invasive DNA collection methods for the first time on wild birds in tropical settings to reconstruct their population genetic structure. I used population genetic modelling to reveal differences among the studied macaw populations, and to relate the genetic structure of the populations to landscape features. I published all seven chapters of my PhD research.

The order Psittaciformes (parrots) contains 398 extant species, divided into 3 families (Psittacidae 374, Cacatuidae 21, Strigopidae 3 species) of which 111 (28%) are classified as threatened on the IUCN Red List. My PhD research presented a wide array of interdisciplinary methods to study parrots: statistical modelling of their extinction risk, on site ecological studies of nest preferences, and population genetic techniques.

I modelled the factors associated with extinction risk in parrots, including intrinsic biological, life history and ecological attributes, external anthropogenic threats, and socio-economic variables of the countries where they occur (Olah et al. 2016, Biodiversity and Conservation). I found a range of significant effects on parrot conservation status including historical distribution size, forest dependency, body size, generation time, the proportion of the human population living in urban areas in the countries encompassing the parrots’ home ranges, per capita GDP of the countries of occurrence, endemism to a single country, and whether the species are used as pets.

Most parrots are obligate secondary cavity nesters, and can be limited in their breeding success by the availability and quality of nest hollows. I evaluated how nesting opportunities for parrots can be increased by provision of artificial nest boxes (Olah et al. 2014, Journal for Nature Conservation). My results show that artificial nests can be used by conservation managers seeking to assist macaw populations where nest hollows are in short supply, and that artificial nests can contribute important data to natural history studies of species where access to natural nests is limited. I showed that Philornis sp. bot fly larvae prevalence was higher in artificial nests than in natural nests. I also described a new field technique of removing Philornis larvae using a snakebite extractor pump (Olah et al. 2013, Veterinary Parasitology).

While extended knowledge about the natural history and ecology of species is crucial for their conservation, by combining ecology and genetics we can reveal new insights not evident from either ecology or genetic studies alone. I developed species-specific microsatellite (STR) genetic markers for scarlet macaw (Ara macao) based on their full genome (Olah et al. 2015, Conservation Genetics Resources). Using these new genetic markers I validated their potential for genetic tagging by using blood samples and moulted feathers of two sympatric macaw species in the Peruvian Amazon (Olah et al. 2016, Conservation Genetics Resources).

I applied non-invasive genetic tagging technique to estimate population size of red-and-green macaws (Ara chloropterus) in the Tambopata region of southeastern Peru (Olah et al. 2017, Conservation Genetics). These conservation genetics techniques can be implemented for other related species with higher conservation concern, while also determining population structure and measuring levels of genetic diversity.

Landscape genetics provide an extra framework to study population dynamics, revealing the landscape factors that contributed to the genetic structure. I used landscape genetic resistance models to confirm isolation by elevation due to the mountain ridges between macaw populations in Candamo (an intermountain valley) and the lowland rainforest of Tambopata (Olah et al. 2017, Landscape Ecology). Maintaining large protected areas and giving conservation priorities for intermountain rainforest valleys are essential for conserving the current genetic diversity of scarlet macaws in Peru.

Download PhD thesis

The following supporters made my PhD project possible: