Author: Francis Wamonje, PhD

On a long train journey from a conference, I spotted a single ant crawling across the table. Instinctively, I flicked it away, much to the chagrin of my travel partner, who had been watching it for some time, entertained by its foraging behaviour. That flick brought me bad karma, as I went on to forget my luggage on the train! The single ant stood no chance against me; however, I have been on the receiving end of ants. In a study in Ghana, we tested the potential of using light traps housed in a sticky, triangular-shaped trap to attract and capture flying pests.

Picture this: a square plot of land with lamps at each corner, each casting a different colour—blue, red, white, and UV. Moths are attracted to light, and this setup was designed to determine the most effective light spectrum for attracting them. From a scientific standpoint, the system was sound. What we had not accounted for were the ants. When you see a single ant near a light trap, you think nothing of it. It registers as background noise, an incidental presence in a system built for something larger, something winged, something visible.

Overnight, the ants figured that the traps with the trapped insects offered easy, stationary, concentrated food. A communication signal was transmitted, and, by sheer teamwork and coordination, they overcame the sticky trap surface. By morning, they had stripped the traps clean. And what’s more, it was not a single ant in play this time, like the one on the train. This time, the ants had strength in numbers, defending, stripping the stuck insects away, holding us at bay.  We had to laugh in frustration and with grudging respect; they were small but mighty.

Here’s the catch: no single ant performs a glamorous, heroic task; instead, they divide the entire action into countless microtasks, move organically, and execute. An ant, on its own, is almost nothing, easily ignored and dismissed. Yet when ants work together, they move objects larger than themselves, build underground cities, and quietly reshape entire landscapes.

This is the power of microtasks.

A microtask is a small, clearly defined unit of work that can be completed without heroics, prolonged effort, or excessive authority, yet, when repeated and shared, contributes to outcomes far larger than itself. In human systems, microtasks are the building blocks of progress. They are the everyday actions that sustain organisations, communities, and societies, even though they rarely attract attention. Answering an email thoughtfully. Recording an observation accurately. Showing up on time. Cleaning a shared space. Passing information along reliably. None of these actions changes the world on its own, but together they do.

Microtasks work because they respect human limits. They recognise that people have finite energy, attention, and time. Rather than demanding constant excellence or continuous urgency, microtasks invite consistency. They lower the barrier to participation and increase the likelihood of completion.

Like ants in a colony, humans function best when responsibility is distributed, effort is shared, and progress is cumulative. Microtasks allow individuals to contribute meaningfully without being overwhelmed and enable systems to move forward without relying on a few exhausted heroes.

The ant is one of the insects I write about in my recent book ‘The Kingdom of Small Things’ To learn more about the simple yet powerful lesson of the ant, pick up a copy, now available on Amazon and on Kindle.

The first time most of us encounter a butterfly, we meet it with wonder. A flash of colour, a moment of stillness. As children, butterflies arrive as beauty. We all remember the first time holding one- the powdery shimmer it leaves on your fingers. A butterfly feels light, fleeting, almost unnecessary, and yet somehow essential.

For scientists, however, the relationship is more complicated. In my own work, butterflies and moths have often entered the story not as symbols but as data points, and sometimes even as problems. In one project in Ghana, we studied the species Leucinodes, a pest of eggplant better known as the Eggplant fruit and shoot borer. The damage was not caused by the adult moth, which is small, almost elegant, and easy to overlook. The destruction came earlier, in the caterpillar stage, hidden deep within the fruit, consuming relentlessly. The irony is striking. The stage that does the damage looks ordinary, even unpleasant. The stage we admire is delicate, winged, and seemingly harmless.

In another project, we are studying the diversity of butterflies following forest restoration in Kenya. Here, butterflies have returned in a different role altogether. They are no longer pests or curiosities but indicators, signals that something in the ecosystem is healing. As the population and diversity of butterflies increase, we know the forest is beginning to breathe again. Same organism. Different meaning. Different role.

And this is where the butterfly becomes more than biology. Scientifically, we know that a caterpillar does not “improve” into a butterfly. It dissolves. Inside the cocoon, much of the old structure breaks down completely. What emerges is not a polished version of the past but something fundamentally new. The caterpillar cannot come with the butterfly.

This is the part we often skip when we speak of transformation. We favour the language of growth. We are less comfortable with the language of loss. But metamorphosis demands surrender. Old habits, identities, and ways of being cannot simply be carried forward. They must be let go, sometimes painfully, sometimes quietly, often invisibly.

In work, careers, organisations, and life, we often cling to caterpillar logic while seeking butterfly outcomes. We want change without dissolution, transformation without discomfort, and beauty without the dark pause of the cocoon. Nature does not work that way.

The butterfly teaches us that becoming requires un-becoming. That some phases of our lives are meant to end completely. That which once consumed and survived must give way to something that serves, pollinates, and moves lightly through the world.

And perhaps that is the deeper lesson: the systems we admire most, forests, fields, and communities, are sustained not by permanent forms but by timely transitions. The caterpillar is necessary. The butterfly is necessary. But they cannot coexist. And so the question the butterfly leaves us with is not whether we want transformation, but whether we are willing to let the old shape dissolve so the new one can emerge.

The butterfly is one of the insects I write about in my recent book ‘The Kingdom of Small Things’ To learn more about the simple yet powerful lesson of the butterfly, pick up a copy, now available on Amazon and on Kindle.

Every breath we take carries invisible traces of life. Fragments of DNA shed by people, plants, animals, fungi, and microbes drift through the air, unnoticed yet abundant. What if we could capture that genetic dust and read the story it holds?  A recent study explores exactly this.

By applying shotgun sequencing to airborne environmental DNA (eDNA), researchers show that it is possible not only to catalogue biodiversity but also to trace populations, track pathogens, and even detect genes linked to antibiotic resistance — all from samples of air.

eDNA has already revolutionised biodiversity monitoring in water and soil, where organisms leave behind genetic traces. Air, however, is a more challenging medium: particles are sparse, dispersed, and easily degraded. Until recently, studies focused mainly on metabarcoding — sequencing short “barcode” fragments of DNA to confirm which species are present.

• Florida, USA – a hammock coastal forest, beaches, and mixed residential sites along the Gulf Coast.
• Ireland – Dublin city centre, mountain ridges, estuaries, and rural locations.

For comparison, they also gathered DNA from water, soil, beach sand, and even windowpanes where airborne particles naturally accumulate.

Air was sampled in several ways: by vacuum pumping air through fine filters, passively exposing filters to natural airflow, or swabbing surfaces where airborne particles had settled. Some samples ran for just hours; others collected DNA over weeks or even months.

In Florida, for instance, DNA fragments from a bobcat (Lynx rufus) were captured in forest air samples. Analysis revealed that this bobcat’s genetic profile clustered with wild and zoo bobcats from northeast Florida — information usually obtained from scat or tissue samples. Similarly, DNA from the golden silk orb weaver spider (Trichonephila clavipes) allowed the team to trace its relationship to other North American populations.

Crucially, genes linked to antimicrobial resistance (AMR) were found across all sample types — air, water, and sand. AMR is one of the World Health Organization’s top global health threats, making the ability to monitor resistance genes in real time a major breakthrough.

Yet not all signals were bad news. Pollinators, including bumblebees and honeybees, were present in several samples. Importantly, DNA from bees and their parasitic mite (Varroa destructor) was found together, offering a way to monitor pollinator health and threats simultaneously.

The potential applications are enormous:

• Conservation – monitoring elusive species and fragile ecosystems.
• Agriculture – detecting crop pests and resistance genes.
• Health – tracking pathogens, allergens, and vectors.
• Forensics – applying genetic insights to law enforcement.
• Drug discovery – mining microbial genomes for new medicines.

Yet with this power comes responsibility. The ability to recover human genetic data from outdoor air demands urgent ethical guidelines and regulatory frameworks. Like artificial intelligence, airborne eDNA is a technology that must be shaped for the public good.

Every gust of wind carries a hidden library of DNA. Thanks to advances in sequencing, we now have the tools to read it. The air, it turns out, is more than what we breathe. It is a shared genetic commons, connecting species and environments in ways we are only beginning to understand.   Harnessing this knowledge wisely could help us face some of the greatest challenges of our time, from biodiversity loss to global pandemics.

Biting midges of the genus Culicoides are tiny, often just 1–3 mm long, but their impact on animal health and agricultural economies can be vast. They vector more than 50 viruses of veterinary concern, including bluetongue and African horse sickness. New Zealand remains free of Culicoides and the diseases they transmit, and it runs a national surveillance programme to keep it that way. This article shares a study that shows advancements in the utilisation of DNA-based tools, specifically DNA metabarcoding of bulk insect samples and environmental DNA (eDNA) recovered from trap fluids to make surveillance faster, more scalable and no less reliable.

Early detection is everything in biosecurity. If Culicoides arrived and established silently, the first sign might be an animal disease outbreak that is both costly and difficult to contain. Yet scanning 15,000–20,000 insects a year by eye is neither efficient nor easily expandable. Molecular approaches promise to read the genetic “fingerprints” of all organisms in a mixed sample in one go, potentially flagging rare or unexpected species that taxonomists might miss.

A brief primer on metabarcoding and eDNA

Metabarcoding is a high-throughput method that uses universal or semi‑universal genetic primers to amplify barcode regions (here, COI) from all organisms present in a mixed sample, which are then sequenced en masse. Bioinformatic clustering of the reads into operational taxonomic units (OTUs) allows rapid estimation of which taxa are present. Environmental DNA (eDNA) refers to the genetic material shed by organisms into their surroundings—water, soil, air, or, in the case of this study, the ethanol inside a light trap—so that it can be captured without handling the organism itself. Both approaches can dramatically reduce the time to screen complex samples, but both come with biases linked to primer choice, DNA degradation, biomass differences and amplification stochasticity.

What the team actually did

The researchers analysed 38 trap samples collected weekly over nine to ten weeks in 2020 from four cattle farms in different North Island districts: Morrinsville, Okaihau, Warkworth and Whakatāne. Each site deployed green LED light traps baited with carbon dioxide and octenol to attract midges and other flying insects. The traps were filled with ethanol to preserve the catch. Every sample was first processed morphologically: insects were counted, and any members of the midge family Ceratopogonidae were recorded. As Culicoides does not occur in New Zealand, native Ceratopogonidae served as a proxy “target group” to test how well the DNA methods could recover what morphology saw and spot what morphology might have missed.

Two parallel molecular routes were then compared. In one, the entire insect catch was homogenised (destroying the specimens) and DNA extracted from the tissue mixture. In the other, DNA was filtered from the ethanol preservative—the eDNA that insects shed into the fluid—leaving the intact specimens available for later taxonomic work if needed. Both DNA types were amplified using two commonly used mitochondrial cytochrome oxidase I (COI) primer pairs (LCO1490/HCO2198 and mlCOIintF/jgHCO2198) and sequenced on an Illumina MiSeq platform. An in‑house Ceratopogonidae COI reference library, supplemented by public databases, supported species assignment.

What the microscope found

Across the 38 trap samples, a total of 45,745 insects were counted. No exotic Culicoides were detected, but native Ceratopogonidae were present in 22 traps (58%), albeit at low abundance—just 114 individuals overall, representing a mere 0.25% of total catch. Most of those were from Whakatāne, where Ceratopogonidae appeared in every sample. These figures served as the benchmark for evaluating molecular performance.

Bulk metabarcoding outperformed eDNA for target detection

When it came to reproducing the morphological verdict on whether Ceratopogonidae were present or absent, metabarcoding of homogenised bulk samples was consistently more accurate than metabarcoding of eDNA from the trap fluid. Using the classic LCO1490/HCO2198 primers, bulk metabarcoding achieved an overall detection accuracy of 81.94%, compared with 68.42% for the ethanol-derived eDNA. With the mlCOIintF/jgHCO2198 primers, bulk metabarcoding again reached roughly the same accuracy (81.58%), while eDNA accuracy dropped to 55.26%. In short, across both primer sets, the bulk approach surpassed the 80% mark, whereas eDNA lagged behind.

False negatives—cases where Ceratopogonidae were seen under the microscope but not detected by sequencing—were the main reason eDNA underperformed. The team also observed a few ‘false positives’, where metabarcoding detected Ceratopogonidae that morphology did not; these could reflect genuinely missed specimens, tiny fragments invisible to the taxonomist, or technical artefacts such as low‑level index “cross‑talk” among samples during sequencing. Importantly, metabarcoding (both eDNA and bulk) did sometimes rescue detections that morphology missed, reminding us that the microscope is not infallible either.

Why did eDNA struggle?

The biology and physics are not in eDNA’s favour here. Ceratopogonidae are extremely small. Small-bodied insects contribute little biomass and therefore little DNA to the preservative ethanol, especially compared with the large moths and flies that dominate trap catches. eDNA is also not evenly distributed through the fluid and can degrade quickly. Even when present, amplification biases during PCR can down‑weight scarce templates further, particularly with broad “universal” primers. Together, these factors make it hard for eDNA metabarcoding to reliably pick up low‑abundance, tiny-bodied targets amid a noisy community background—at least with generalist primers and the workflows used here.

Primer choice shaped the community picture more than sample type

Although eDNA was weaker for yes/no detection of Ceratopogonidae, both molecular approaches painted broadly similar pictures of the overall insect communities in each trap. Non-metric multidimensional scaling showed that ethanol and bulk samples from the same trap usually clustered together, meaning they recovered comparable community structure. What did make a bigger difference was the primer pair. LCO1490/HCO2198 skewed strongly towards Lepidoptera, whereas mlCOIintF/jgHCO2198 yielded a more even spread across orders such as Lepidoptera, Diptera and Trichoptera. This reinforces a central truth of metabarcoding: your primers define your window on biodiversity.

So, what value does eDNA bring?

Despite its lower sensitivity for the specific, tiny-bodied target group tested here, eDNA retains several important advantages. It is non‑destructive, allowing taxonomists to re‑examine the original specimens. It is operationally simpler—filter the fluid, extract DNA, and you can process far more samples more quickly than microscopy allows. It produces community‑level data that align well with bulk metabarcoding, so it can still track spatial and temporal shifts in insect assemblages at scale. Crucially, eDNA’s performance could be markedly improved if the aim is targeted detection rather than broad community profiling—for example, by switching from metabarcoding to quantitative PCR (qPCR) or digital PCR assays that lock onto Culicoides‑specific markers with much higher sensitivity. In other words, use eDNA metabarcoding to understand the community and screen widely, then deploy species‑specific assays to decisively confirm or rule out incursions.

Practical implications for biosecurity programmes

For routine, rapid, early‑warning surveillance of unwanted midges, bulk-sample metabarcoding currently delivers the best balance of accuracy and throughput when using universal COI markers. Where preserving specimens is essential, an eDNA-first workflow could facilitate triage of samples: rapidly screen trap fluids to flag suspect traps, then prioritise those specimens for either bulk metabarcoding, species-specific qPCR, or morphological confirmation. Programmes should also invest in well-curated, regionally comprehensive reference libraries (the in-house Ceratopogonidae database used in this study was invaluable) and in validating primer sets against the taxa of greatest concern.

Conclusion

This study offers a measured, practice‑ready message. If your immediate need is to know, with high confidence, whether a delicate, low‑abundance target like Ceratopogonidae is present in a trap, homogenised bulk metabarcoding with carefully chosen primers currently does the job better than ethanol‑derived eDNA. But if your goal is to scale surveillance, keep specimens intact, and track whole insect communities efficiently, eDNA metabarcoding of trap fluids is already useful, and with species‑specific assays layered on top, it could become a powerful, non‑destructive frontline tool for early detection.

The health of honey bee populations underpins both global agriculture and ecological resilience. Among the many threats facing bees, the parasitic mite Varroa destructor has become a particular focus of international concern. This tiny yet devastating pest weakens colonies, transmits viruses, and contributes to significant losses in managed bee populations worldwide.

The recent arrival of Varroa destructor in Australia, a country that had previously remained free of the mite, has underscored the urgent need for effective detection and biosecurity measures. Timely identification of infestations is critical for protecting both agricultural productivity and biodiversity. In this context, a promising innovation is emerging: the use of environmental DNA (eDNA) as a tool for monitoring V. destructor.

This article shares recent research that investigates the application of eDNA methods for detecting Varroa destructor within honey bee hives, offering a complementary approach to traditional techniques. The findings suggest that eDNA-based detection could enhance surveillance, support early interventions, and contribute to safeguarding pollinator health globally.

Why Early Detection Matters

Honey bees play an essential role as pollinators of both crops and wild plants. Their decline poses risks not just to agricultural yields, but to the integrity of ecosystems more broadly. The spread of Varroa destructor has exacerbated this challenge. By feeding on bees and facilitating the transmission of pathogens, the mite undermines colony health, disrupts pollination services, and amplifies the vulnerability of already stressed bee populations.

Traditional methods for detecting V. destructor, such as alcohol washes, are widely used by beekeepers but involve handling bees directly, which can disturb colonies and require considerable effort and expertise. These approaches are reliable but not ideally suited for frequent, large-scale surveillance, particularly when rapid response is needed.

Environmental DNA: A New Approach

Environmental DNA refers to genetic material that organisms shed into their surroundings, through skin, saliva, faeces or, in this case, hive debris and honey. By sampling and analysing this DNA, researchers can detect species without needing to observe or capture them directly.

eDNA methods offer several distinct advantages. They are non-invasive, reducing the need to handle bees and disrupt colonies. The techniques are also highly sensitive, capable of detecting low levels of pest DNA that might indicate an incipient infestation. Moreover, eDNA sampling is scalable, as it can be employed across multiple sites relatively quickly and without the need for extensive specialist training, making it attractive to both beekeepers and biosecurity authorities.

Developing the Molecular Assay

At the heart of this study was the development of a species-specific quantitative PCR (qPCR) assay, designed to target the mitochondrial cytochrome oxidase (cox1) gene of Varroa destructor. This gene provides a unique signature, enabling precise identification of mite DNA even amidst the complex biological material present in a hive.

To ensure reliability, the assay was rigorously tested against DNA from closely related mite species and honey bee hosts. This step was essential for confirming specificity and avoiding false positives. Optimisation of the assay parameters included careful calibration of primer and probe concentrations to maximise sensitivity.

All assays were performed using a modern real-time PCR platform, ensuring robust and reproducible detection.

Sampling Inside the Hive

The research deployed a sampling strategy designed to capture eDNA from multiple sources within honey bee colonies. Honey, in particular, was recognised as a valuable substrate. Collected from capped combs using sterile techniques, honey provides a medium where mite DNA can accumulate over time, effectively recording the history of infestation.

Swabs were taken from hive entrances and brood frames, targeting surfaces where mites or their traces might be deposited by foraging and nursing bees. To ensure accuracy, negative control samples were collected at each sampling site to monitor for contamination.

Comparing eDNA with Traditional Techniques

To evaluate the effectiveness of eDNA detection, the researchers compared their findings with those obtained through the alcohol wash method. In this conventional approach, around 300 adult bees are immersed in ethanol, dislodging mites for counting. While robust, this method is inherently invasive and labour-intensive.

Statistical analyses, including McNemar’s Chi-square test, were used to assess the agreement between the two approaches, providing a quantitative measure of eDNA’s performance relative to established practice.

Key Findings

The study revealed that eDNA methods can offer a highly sensitive means of detecting Varroa destructor. Among the different sample types, honey consistently yielded the highest detection rates, with sensitivity measured at 91%. This outperformed swabs from hive entrances and brood frames, whose sensitivities were considerably lower.

Importantly, the number of mite DNA copies detected in honey samples increased with infestation levels, suggesting that eDNA quantification could offer insights not only into presence or absence, but also into the scale of infestation. Such information is valuable for beekeepers aiming to tailor interventions appropriately.

However, the study also noted limitations. Detection rates declined at very low infestation levels (below 1%), indicating that eDNA sensitivity is diminished when mite populations are just beginning to establish. This finding highlights the need for further optimisation, especially if eDNA is to be deployed as an early warning system.

The results highlighted that while swabs from hive entrances and brood frames provided valid supplementary data, they lacked the consistency shown by honey samples. A combined approach, drawing on both honey sampling and surface swabbing, may prove to be the most effective.

Implications for Biosecurity and Beekeeping

The potential applications of eDNA techniques in biosecurity surveillance are significant. Their non-invasive nature reduces stress on bee colonies. At the same time, their scalability allows for broader monitoring coverage—qualities that are particularly valuable when surveillance needs to be expanded rapidly, such as during an incursion into previously mite-free regions.

By complementing, rather than replacing, traditional methods, eDNA detection can enhance the overall surveillance toolkit available to beekeepers and regulators. Alcohol washes will remain important for estimating infestation intensity within colonies, but eDNA provides an additional, sensitive means for early detection.

For Australia and other regions still striving to keep Varroa destructor at bay, eDNA offers a means of detecting incursions promptly, buying time for containment and eradication efforts before the mite becomes established.

Looking Ahead

This research opens the door to further exploration of how eDNA methods can contribute to supporting pollinator health. Collaboration will be key: researchers, beekeepers, biosecurity authorities and policymakers will need to work together to ensure that eDNA tools are developed, validated and deployed effectively. Future work could focus on improving sampling protocols, investigating the persistence of mite DNA in hive environments, and extending the approach to monitor other pests and pathogens relevant to honey bee health.

Pollinator health is under increasing pressure. Innovations such as these represent not just technical progress but a vital contribution to securing the future of both food production and ecological stability.