The research, led by Alberto Perelló of the Instituto de Investigación en Recursos Cinegéticos and João Queirós of the University of Porto, was motivated by a pressing problem. Livestock-wildlife interfaces are hotspots for pathogen transmission between domestic and wild animals, and understanding which species are present is the first step toward managing disease risk. Grazing livestock currently occupies roughly half of the world’s agricultural land, while several wildlife species have expanded dramatically due to changes in management, climate and habitat. This convergence creates abundant opportunities for interaction, particularly around limited water sources during the dry Mediterranean summer, when animals aggregate and pathogens can accumulate at shared drinking points.

To evaluate monitoring approaches, the team deployed 27 to 30 camera traps at each of the 13 farms, positioning them preferentially at high-risk locations such as food and water resources, with the remainder distributed randomly. The cameras operated continuously for two consecutive days, capturing three rapid-fire images per activation. In parallel, researchers collected water from one lentic water body per site, including artificial ponds and livestock watering troughs, filtering it through specialized capsules designed to capture DNA. The filtration process yielded an average of just over 10 liters of water per site, processed in roughly 18 minutes.

In the laboratory, the team extracted DNA from the filtration capsules and amplified a region of the 12S rRNA gene using the Vert01 primer set, which targets vertebrates broadly. The amplified DNA was then sequenced on an Illumina MiSeq platform, generating between 56,376 and 867,234 reads per study site. Bioinformatic processing with OBITools software removed low-quality sequences and assigned taxonomy by comparing the remaining reads against a local reference database of Iberian vertebrate species. Contaminants and sequences below a 0.1 percent abundance threshold were filtered out to minimize false positives.

The results revealed a clear asymmetry. Camera traps detected significantly higher taxa richness than eDNA for wild mammals, total mammals and birds. Wild mammal richness averaged 7.84 taxa per site using cameras versus just 2 via eDNA, while bird richness averaged 7.61 versus 0.85. Of the 22 mammal taxa detected across all sites when combining both methods, only nine were detected by both approaches in at least one location, with coincidence between methods ranging from 11 to 85 percent depending on the site. No bird taxa were detected by both methods at any site.

Perhaps most intriguingly, the study found that species ecology shaped detection patterns in opposite ways depending on the method. Camera traps recorded significantly higher relative detection rates for non-gregarious taxa, such as solitary carnivores like the red fox and European badger, averaging 51.31 relative abundance compared to 31.51 for gregarious species. eDNA showed the reverse pattern, with gregarious taxa, including livestock and wild ungulates, dominating the molecular signal at 83 percent relative read abundance versus just 0.10 percent for non-gregarious taxa. The researchers caution that this association likely reflects taxonomic identity, abundance, biomass and frequency of water point use rather than gregarious behavior itself, since the gregarious category was dominated by livestock and ungulates while non-gregarious mammals were mostly carnivores.

The eDNA data revealed that 88 percent of total reads and 54 percent of operational taxonomic units corresponded to mammals, with 99.68 percent of mammal reads assigned to the order Artiodactyla, the even-toed ungulates that include cattle, sheep, goats, pigs and deer. Within this group, cattle accounted for 55 percent of reads and wild boar for 28 percent, reflecting the overwhelming contribution of abundant, water-associated species to the environmental DNA pool. Amphibians were detected at 10 of 13 sites, reptiles at only 2 sites, and a single fish species at 5 sites.

Beyond species detection, the study explored whether livestock density influenced the molecular characteristics of water samples. Linear models showed that livestock density was significantly associated with both DNA concentration measured by Qubit fluorometer and the A260/230 purity ratio measured by Nanodrop spectrophotometer. However, the authors urge caution in interpreting these findings, as Qubit measurements quantify total double-stranded DNA rather than vertebrate DNA specifically, meaning the observed relationships cannot be directly attributed to increased availability of target genetic material.

The researchers acknowledge several limitations. The eDNA sampling was restricted to a single water point per site with two filtration replicates, while camera traps covered a substantially broader area. The molecular marker used could not distinguish between domestic pigs and wild boar, both identified as Sus scrofa, complicating interpretation at pig-dominated farms. The study also did not employ occupancy models to account for imperfect detection, and the relatively small number of 13 study sites limits statistical power and generalizability.

Despite these constraints, the findings carry important implications for wildlife monitoring programs in livestock-dominated environments. The lack of concordance between camera trapping and eDNA at the site level underscores that these methods capture complementary aspects of biodiversity rather than interchangeable measures of the same thing. Relying exclusively on eDNA-based techniques risks producing biased biodiversity estimates in these settings, as the genetic signal from abundant taxa that frequently visit water points may drown out the presence of rarer or more elusive species. The authors recommend combining both approaches within an integrated wildlife monitoring framework, leveraging the strengths of each to build a more complete picture of the vertebrate communities that share these working landscapes, and ultimately to inform biosecurity strategies that reduce the risk of cross-species pathogen transmission.

Subject of Research: Comparative performance of environmental DNA metabarcoding and camera trapping for biodiversity monitoring at livestock-wildlife interfaces in the Iberian Peninsula

Article Title: Environmental DNA metabarcoding performance for biodiversity monitoring at livestock–wildlife interfaces

Article References: Perelló, A., Martins, F. M. S., Pérez-Sancho, M., Relimpio, D., Herrero-García, G., Díez-Guerrier, A., Marín-Rojo, Á., Alves, P. C., Gortázar, C., & Queirós, J. (2026). Environmental DNA metabarcoding performance for biodiversity monitoring at livestock–wildlife interfaces. Frontiers in Ecology and Evolution, 14, Article 1933292. https://doi.org/10.3389/fevo.2026.1933292

Image Credits: AI Generated

DOI: 10.3389/fevo.2026.1933292

Keywords: environmental DNA, eDNA metabarcoding, camera trapping, livestock-wildlife interface, biodiversity monitoring, Iberian Peninsula, wildlife disease surveillance, gregarious species, pathogen transmission, One Health, vertebrate detection, Mediterranean ecosystems

For decades, the dominant mathematical descriptions of mosquito dispersal have belonged to two families: reaction–diffusion equations, which treat mosquito populations as continuous densities that spread smoothly across space, and patch-based metapopulation models, which exchange mosquitoes between habitat patches according to simple flux assumptions. Both approaches have been enormously productive, underpinning predictions of pathogen spread and the planning of control interventions. But they share a critical simplification. In each, the emigration of mosquitoes from one location to another is treated as a statistical process, a flux governed by distance and density, rather than as the outcome of individual insects making decisions.

The new work takes the opposite approach. Sánchez C. and his collaborators built two behavioral state microsimulation models, computational frameworks in which each simulated mosquito occupies a discrete behavioral state—searching for a host, seeking aquatic habitat to lay eggs, looking for sugar, resting—and must locate the resources it needs on a model landscape. Movement in these models is not prescribed by a diffusion coefficient. Instead, individual mosquitoes execute sequences of flights, guided by simple rules of detection and orientation, and population-level dispersal arises as an emergent property of countless individual searches. The shift is conceptually significant: dispersal is no longer an input to the model but a phenomenon the model must explain.

Models of this kind are notoriously laborious. Defining behavioral states, resource distributions, transition rules, and movement mechanics by hand, then solving and analyzing the resulting simulations, is a bottleneck that has kept microsimulation out of mainstream mosquito ecology. To remove that obstacle, the team developed ramp.micro, an open-source R package for building, solving, analyzing, and visualizing behavioral state microsimulation models for mosquitoes. The package, which integrates with the broader R Analysis Platform for Mosquitoes ecosystem, allows researchers to specify landscapes, resource distributions, and mosquito life histories, then run simulations and dissect the resulting movement patterns with reproducible workflows.

The payoff of the behavioral approach is a set of findings that challenge standard intuitions about mosquito dispersal. The most striking concerns population structure. When the authors analyzed simulated mosquito movement patterns with crude statistical tools of the sort often applied to field data, the underlying behavioral structure of the population was not revealed. Mosquitoes that differed sharply in their behavioral states and flight histories could appear, from a coarse snapshot of positions, to belong to a single well-mixed swarm. Only analyses that account for sequences of flights—individuals progressing through behavioral states while trying to accomplish specific goals—exposed the true structure lurking beneath the surface.

This result carries a caution for empirical studies. Mark–release–recapture experiments and genetic estimates of dispersal typically summarize movement as distances traveled or rates of spread, collapsing the rich temporal structure of individual flight sequences. If that structure matters, as the simulations suggest it does, then some of the apparent disagreement among field estimates of mosquito dispersal may reflect not biological variation but measurement artifacts: the same population can look structured or unstructured depending on how its movement is summarized. The study implies that inferring dispersal from observed positions alone risks missing the very organization that governs how pathogens and genes actually move through mosquito populations.

A second finding is equally consequential. Even when the team distributed resources randomly and uniformly across the landscape—with no environmental features, no water bodies, no clusters of hosts, no habitat heterogeneity of any kind—simulated mosquito populations spontaneously formed highly structured spatial communities. Structure emerged from behavior rather than from the environment. The mechanism is intuitive once stated: a mosquito that finds resources returns repeatedly to the places where it found them, and the patchy geometry of individual search histories, aggregated across many insects, breaks the uniformity that the landscape itself possesses. Local searching behavior, in other words, manufactures spatial organization from nothing.

The authors push the analysis further by showing that some of the heterogeneity in simulated mosquito densities can be attributed to properties of a network defined by searching itself. In this view, each mosquito’s sequence of flights traces a path through the landscape connecting the resources it visits, and the aggregate of these paths forms a network whose nodes are resource locations and whose links are realized search trajectories. The topology of this search network—which locations are commonly visited together, which remain isolated from the bulk of movement—predicts where mosquitoes accumulate. Dispersal, on this account, is not merely a property of distance and density but of connectivity generated by how insects search for what they need.

For mosquito-borne pathogen transmission, these dynamics are anything but academic. The intensity of malaria, dengue, and other vector-borne transmission depends critically on how vectors are distributed relative to susceptible hosts, and on how quickly mosquitoes colonize new habitat after interventions such as larval source management or insecticide spraying. Models that assume smooth diffusive spread may misrepresent both processes. If real mosquito populations, like the simulated ones, form tightly structured local communities even in homogeneous environments, then transmission hotspots and barriers to gene flow could arise without any visible environmental cause. Conversely, ignoring resource availability as a driver of movement could lead control programs to misjudge how far and how fast resistant genes, or suppressive gene drive constructs, will spread after release.

The study’s authors argue that the broader lesson is the importance of local context. A mosquito’s movement is shaped not only by how far it can fly but by what it can find, where it can find it, and what behavioral state it happens to occupy when it sets out. Spatial models for mosquito ecology and pathogen transmission, they conclude, would benefit from treating resource availability as a first-class factor affecting movement and dispersal, rather than folding it implicitly into background parameters. The ramp.micro package is offered as a practical step in that direction, giving researchers the tools to build mimetic, behaviorally explicit models without the engineering burden that previously made such models impractical. If the approach scales from simulation to field-relevant landscapes, it may force a reconsideration of what field measurements of mosquito dispersal actually measure—and reveal that the geography of disease is written, in large part, in the searching behavior of a few millimeters of insect.

Subject of Research: Behavioral state microsimulation modeling of mosquito dispersal and resource searching

Article Title: Mosquito dispersal in context

Article References: Sánchez C, H. M., Wu, S. L., Henry, J. M., Guerra, C. A., Galick, D. S., Garcia, G. A., Marshall, J. M., & Smith, D. L. (2026). Mosquito dispersal in context. PLOS Complex Systems, 3(6), e0000108. https://doi.org/10.1371/journal.pcsy.0000108

Image Credits: AI Generated

DOI: 10.1371/journal.pcsy.0000108

Keywords: mosquito dispersal, behavioral states, microsimulation, ramp.micro, PLOS Complex Systems, reaction-diffusion models, resource availability, spatial structure, mosquito ecology, pathogen transmission, population models, search behavior

These sacs are called expelled food vacuoles, or EFVs. When a protozoan such as the ciliate Tetrahymena feeds, it engulfs bacteria into food vacuoles, compartments that normally mature into digestive vacuoles filled with the acidic enzymes and molecular machinery needed to dismantle their cargo. In many cases, that is exactly what happens, and the bacterium is destroyed. But a growing list of bacterial species has evolved the ability to resist this digestive programme. Rather than being killed, the survivors remain inside the vacuole, which the protozoan then expels intact. Earlier studies referred to these expelled structures by a variety of names, including expelled vesicles, faecal pellets and multilamellar bodies, and often regarded them as little more than the discarded refuse of protozoan digestion. The new review contends that this interpretation has understated their importance.

The central claim of the review is that EFVs should be understood as biologically generated reservoirs: protective containers that package viable pathogenic bacteria and release them into the environment already primed for persistence, dissemination and host colonisation. Far from being waste, these structures behave like miniature transport capsules, each one shielding its bacterial passengers from a hostile outside world. The authors describe this as a distinct environmental transmission state, a phase of a pathogen’s life in which it is neither free-swimming in water nor established inside a host, but travelling in a self-contained vehicle manufactured by another organism.

The evidence for this concept comes from a strikingly diverse set of pathogens. The review gathers findings from studies of Vibrio cholerae, the agent of cholera; Salmonella enterica, a leading cause of food poisoning; Legionella pneumophila, the cause of Legionnaires’ disease; Campylobacter jejuni, a common cause of gastroenteritis; Listeria monocytogenes, which can cause severe disease in pregnant people and the immunocompromised; Escherichia coli; the opportunistic pathogen Burkholderia cenocepacia; and the soil bacterium Mycobacterium smegmatis, a widely used model for tuberculosis research. Across these very different organisms, a common pattern emerges: bacteria that have passed through protozoa and emerged inside EFVs display measurable increases in resistance to stresses that would normally kill them.

The protective effects documented in the literature are broad. EFV-associated bacteria withstand acid exposure better than their free-living counterparts, an advantage that matters enormously when a waterborne pathogen confronts the acidic environment of the human stomach. They also survive starvation for longer periods, tolerate disinfectants and biocides, resist oxidative stress, and endure desiccation. In practical terms, a cholera bacterium packaged inside an expelled vacuole can persist in a drying pond, in treated drinking water, or on a contaminated surface for far longer than one floating alone, and it arrives at the next host in a hardier condition. The review also highlights reports of enhanced infectivity among EFV-associated pathogens, suggesting that the vacuolar packaging does not merely prolong survival but may actively prime the bacteria for subsequent colonisation of new hosts.

One of the most consequential findings relates to horizontal gene transfer, the process by which bacteria exchange genetic material. Because multiple bacteria can be concentrated inside a single small vesicle, EFVs create crowded micro-environments in which cells sit close together in fluid enclosed by a membrane. This physical intimacy facilitates the exchange of plasmids and other genetic elements, potentially accelerating the spread of antibiotic resistance genes through environmental microbial communities. In an era when antimicrobial resistance is recognised as one of the greatest threats to global public health, the possibility that protozoan predators inadvertently act as genetic mixing vessels for pathogens is a finding with far-reaching implications.

The review’s authors frame their synthesis around a conceptual shift. If EFVs are merely waste, then monitoring programmes that count free bacteria in water may be missing a hidden reservoir of infectious agents entirely. But if EFVs are vehicles of transmission, as the accumulated evidence suggests, then they represent a measurable and potentially targetable stage in the life cycle of environmental pathogens. The authors propose that EFV-associated pathogens could serve as useful targets for water surveillance and outbreak prediction. Detecting these vesicles in reservoirs, drinking water systems, or recreational waters could provide an early warning that a pathogen population has entered a particularly durable and transmissible state, before cases begin to appear in clinics.

This perspective also reframes the ecological relationship between protozoa and bacteria. The traditional view holds that protozoan grazing suppresses bacterial populations, acting as a check on microbial growth. The EFV concept reveals a paradox at the heart of that relationship: the predator that kills most bacteria may simultaneously serve as an incubator and distributor for the few that can resist digestion. In effect, protozoa may function as accidental selective agents, culling susceptible cells while packaging the resistant ones for wider dispersal. Over evolutionary time, this could help explain why so many environmental pathogens, including Legionella and various non-tuberculous mycobacteria, show an inherent ability to survive inside protozoa and, later, inside human cells. The machinery that lets a bacterium resist digestion in a Tetrahymena vacuole may be the same machinery that lets it resist killing by macrophages, the immune cells that patrol human tissue.

The authors are careful to present their synthesis as a framework rather than a settled conclusion, and they call for the field to move past the fragmented terminology of earlier decades and treat expelled food vacuoles as a unified object of study. Doing so, they argue, will allow researchers to connect environmental persistence with infection biology in a single mechanistic story: a pathogen that survives protozoan digestion exits the predator inside a protective vesicle, persists longer in the environment, resists treatment more effectively, exchanges genes more readily, and colonises new hosts more successfully. For public health authorities, the message is that the journey of a waterborne pathogen between hosts may be far more sophisticated than previously appreciated, and that the humble vacuole, long dismissed as refuse, may hold keys to predicting and preventing outbreaks. For microbiologists, the review opens a research agenda in which the ecology of single-celled predators and the epidemiology of human disease are inseparable parts of the same system.

Subject of Research: Expelled food vacuoles produced by protozoa as protective vehicles that promote bacterial persistence, stress resistance, gene transfer and transmission of pathogens

Article Title: Expelled Food Vacuoles as Protozoan-Derived Vehicles for Bacterial Persistence and Transmission

Article References: Faruque, S. N., Ponton, I. A., Moon, J. M., & Espinoza-Vergara, G. (2026). Expelled Food Vacuoles as Protozoan-Derived Vehicles for Bacterial Persistence and Transmission. Microbial Ecology. https://doi.org/10.1007/s00248-026-02880-6

Image Credits: AI Generated

DOI: 10.1007/s00248-026-02880-6

Keywords: protozoa, expelled food vacuoles, bacteria, Vibrio cholerae, Legionella pneumophila, Tetrahymena, water surveillance, antibiotic resistance, horizontal gene transfer, pathogen transmission, microbial ecology, environmental persistence