At least 25 ant taxa had been reported from Kamchatka in publications extending back more than a century, but the historical lists disagreed about which species were present. The researchers reviewed 14 literature sources containing substantial information about ants in the region and divided records into two reliability categories. Twelve species were classified as reliable because they were supported by at least two independent sources, including sources published within the previous two decades. These species belonged to four genera: Camponotus, Formica, Leptothorax and Myrmica.

The other 13 reported species and the genus Lasius were classified as questionable. Their records came from either single or dated sources and were contradicted by more recent work. The study noted that disagreements in older lists could reflect incorrect collection information, taxonomic revisions or misidentifications, but the evidence did not establish which explanation applied to each disputed record.

Manual fieldwork in 2016 at eight localities found nine ant species from sea level to approximately 1,000 metres above sea level. The ants occurred in lowland meadows, stone birch forests, larch and birch forests and the dwarf-pine zone. No ants were observed in alpine tundra or plantless habitat above 1,200 metres. Larch and birch forests at intermediate elevations contained the largest number of species, whereas low-elevation stone birch forests contained only three observed species. Among the nine field-collected taxa, three had Holarctic, three trans-Palearctic and three East Palearctic distributions.

For the genetic component, the researchers generated mitochondrial COI barcodes for 47 specimens and combined them with 10 previously published sequences, producing a dataset of 57 sequenced specimens. High-quality barcodes distinguished all nine species with a clear barcode gap. Interspecific raw genetic distances ranged from 2.3% between Formica candida and F. gagatoides to 22.5% between Camponotus herculeanus and Leptothorax acervorum.

Genetic variation within most species was low. Six of the nine species had only one COI haplotype, while Formica lemani and Myrmica displicentia had two each. L. acervorum was the exception: its seven sequenced specimens each had a different haplotype, two haplogroups were detected, and within-species raw distances ranged from 0.15% to 2.13%. One specimen belonged to a haplogroup previously known only from North America. The authors presented a long-term refuge in Kamchatka and long-distance dispersal of the species’ small sexual castes as possible explanations, not established causes.

Comparisons with the Barcoding of Life Data System showed that every Kamchatka haplotype except one had not been recorded elsewhere in the database at the time of the analysis. The exception was the sole haplotype found in Formica lugubris, which also occurred in Finland. Closely related sequences were found for the three Holarctic species in North America, or in both Europe and North America, indicating a closer genetic association across Beringia than between western and eastern Palearctic populations for those taxa. By contrast, the East Asian Myrmica species M. displicentia and M. kamtschatica had their closest available matches in unidentified Myrmica specimens from the Russian Far East.

A separate morphometric analysis examined 110 Formica specimens to determine whether Kamchatka workers that resembled F. fusca or F. lemani represented one or both species. The analysis included 34 Kamchatka workers, 33 European F. lemani and 43 European F. fusca. A published discriminant placed the Kamchatka workers between the European reference groups: 68% produced negative values, as European F. fusca, and 32% produced positive values, as European F. lemani. These values were results of the composite discriminant and did not directly measure the presence or absence of pronotal setae.

The study classified the Kamchatka ants as F. lemani, with the qualification that a future treatment of the taxa as one species would give priority to the older name F. fusca. Specimens assigned to both morphologies occurred in the same nests, and no nest contained only workers with the F. lemani pattern. All but one sequenced colony shared the same COI haplotype, while the remaining sequence differed by one nucleotide, or 0.15%. All three available Kamchatka gynes had discriminant values and a shiny first tergite consistent with F. lemani; in F. fusca, that tergite is covered by dense pubescence and appears matt. Two of the gynes shared nests with workers assigned the F. fusca pattern. Previous work using nuclear microsatellites, mitochondrial COI and Cyt-b had also not separated the two taxa, leaving their taxonomic relationship unresolved.

The authors cautioned that the checklist of 12 reliable species is conservative because Kamchatka is large and most of it remains poorly explored. The study was also geographically and temporally limited: field sampling covered eight localities in one year, while the DNA analysis represented nine species and 57 specimens. Its clearest conclusions are therefore the separation of reliable from questionable records, documentation of nine species across the sampled habitats, the distinct barcodes among those nine taxa and the limited genetic diversity observed within most of them.

Subject of Research: Taxonomic, ecological and mitochondrial genetic assessment of ants in Kamchatka

Article Title: Ants of Kamchatka: checklist, DNA-barcoding and key ( Hymenoptera , Formicidae )

Article References: Schär, S. (2024). Ants of Kamchatka: checklist, DNA-barcoding and key (Hymenoptera, Formicidae). Alpine Entomology, 8, 19-28. https://doi.org/10.3897/alpento.8.114185

Image Credits: AI Generated

DOI: 10.3897/alpento.8.114185

Keywords: Kamchatka ants, species checklist, DNA barcoding, COI haplotypes, Formica taxonomy, Leptothorax acervorum, Myrmica, ant biogeography, field survey, Ants, Kamchatka, checklist

The physics underlying the approach centers on subduction zones, the convergent plate boundaries where one tectonic plate slides beneath another. These settings produce the planet’s largest earthquakes, including events exceeding magnitude 8.5, and frequently unleash devastating tsunamis when the seafloor lurches upward or sideways. But not every part of a subduction interface moves the same way. Some patches slip freely and harmlessly as the plates grind past one another, while others remain firmly stuck, a state scientists call locking. These locked patches, known as asperities, behave like patches of high friction that resist motion even as the plates around them continue to converge. Year after year, the surrounding crust deforms to accommodate the accumulating mismatch, storing elastic strain energy like a slowly winding spring. When the frictional resistance finally fails, that stored energy is released in seconds as a major earthquake. The Riverside team’s insight was that this years-long accumulation phase leaves a measurable fingerprint at the surface, and that fingerprint can be detected and mapped before rupture.

The fingerprint in question comes from GPS. Networks of continuously operating ground stations scattered across subduction-zone coastlines record millimeter-scale movements of the Earth’s surface as the crust flexes in response to a locked fault below. Where the interface is locked, coastal points are typically dragged landward or held back relative to the motion expected from steady plate convergence; where it creeps, the surface moves more freely. By inverting these subtle deformation patterns, the researchers developed a new algorithm that distinguishes locked, energy-storing portions of the fault from freely slipping ones. The technique does not require dense or perfect data. As Periollat noted, the team had identified the Kamchatka asperity based on a relatively limited data set, and the model still pinpointed the region that later broke. That robustness matters, because offshore faults are among the most poorly instrumented places on the planet, and any forecasting method must work with sparse observations to be practically useful.

The Kamchatka test case is the study’s most dramatic result. Before the rupture, the researchers’ analysis of GPS measurements had highlighted a specific locked region beneath Russia’s Kamchatka Peninsula as a zone of concentrated strain accumulation. The timing of any eventual earthquake was beyond the scope of their method, and they make no claim to have predicted when the event would occur. But when a giant earthquake did strike in 2025, the rupture occurred exactly where the model indicated strain had built up. “We had an idea where the strain was accumulating based on a relatively limited data set,” Periollat said. “Seeing it work so well confirmed that this approach has real potential.” For a field in which retrospective claims of predictive success are often contested, a documented forecast of a rupture location made before the event stands out as an unusually clean validation.

Equally instructive is what the comparison with history revealed about how differently earthquakes can behave at the same boundary. Kamchatka experienced giant earthquakes in both 1952 and 2025, yet the more recent event generated a much smaller tsunami. The researchers interpret this contrast as evidence that the shallowest portion of the fault slipped less during the 2025 rupture than it did during the earlier one. Because shallow slip on a subduction interface displaces the seafloor most efficiently and is a primary driver of tsunami generation, this difference in rupture behavior carries direct hazard implications. The finding underscores a key limitation the team is careful to state: the method identifies where strain is stored, not how a future rupture will distribute that slip, and it cannot predict tsunami size or earthquake timing. Even so, knowing which segments of a megathrust are primed to break narrows the search space for hazard assessment considerably.

The practical value of location-specific forecasting lies in long-term planning rather than short-term warning. Building codes, evacuation routes, tsunami inundation maps, and infrastructure investment all depend on knowing which stretches of coastline face the greatest risk. A method that can rank fault segments by their stored strain gives planners a physically grounded basis for prioritizing those decisions. The Riverside team is already extending the approach to other major subduction zones in Japan, Mexico, New Zealand, and the Pacific Northwest, each of which presents additional complications. Some of these boundaries host slow-slip events that release accumulated energy gradually rather than in sudden earthquakes, blurring the simple distinction between locked and creeping patches and demanding more sophisticated models of how strain builds and dissipates over time.

The researchers are also testing whether the same framework can be applied to continental transform faults closer to home. “In the Bay Area, the Hayward Fault has both creeping and locked sections, much like subduction zones,” Funning said. “We’re investigating whether we can identify the parts most likely to generate future earthquakes.” The parallel is scientifically appealing: if the algorithm can resolve locking along a strike-slip fault threaded through a densely populated urban corridor, it could sharpen hazard estimates for millions of residents. The Hayward Fault creeps visibly along much of its length, yet historical and paleoseismic evidence shows it is capable of large ruptures, making the question of which sections remain truly locked a matter of considerable public interest. Translating a method validated at a subduction zone to a different faulting regime will require careful adaptation, but the underlying principle of mapping surface deformation to infer subsurface locking applies broadly.

Scaling the technique globally, however, runs into an observational bottleneck. GPS stations on land provide valuable information, but many of the world’s most dangerous faults lie offshore, beneath the ocean, where conventional ground-based geodesy cannot reach. Researchers in Japan have begun deploying acoustic instruments on the seafloor that combine underwater sound travel times with satellite positioning to measure slow deformation over many years, and similar efforts are being proposed for Chile and the Pacific Northwest. A recently launched satellite could eventually provide additional geodetic measurements in regions that currently lack GPS coverage, extending the method’s reach. The work also highlights major gaps in global earthquake monitoring, particularly in parts of the Pacific where sparse data make it difficult to assess tsunami hazards. Closing those gaps, the authors argue, is a prerequisite for applying strain-based forecasting to the plate boundaries that need it most.

Throughout, the team is emphatic that improved forecasting of earthquake locations should complement, never replace, public preparedness. “Your peace of mind shouldn’t come from believing we can forecast the exact earthquake,” Funning said. “Especially where we live in Southern California, it’s not a matter of if, but when. There is no substitute for preparation.” That message frames the study’s contribution in sober terms: the algorithm cannot tell a coastal community the day or hour of the next megathrust rupture, but it can tell engineers and emergency managers where the spring is most tightly wound. “We can identify where large earthquakes are likely to occur, even if we can’t predict exactly when,” Periollat said. “With better observations and continued monitoring, we can learn much more about Earth’s most dangerous faults.” If the method performs as well at other plate boundaries as it did at Kamchatka, the map of future earthquake risk may become considerably sharper, one locked asperity at a time.

Subject of Research: A GPS-based method for identifying locked fault segments where giant subduction-zone earthquakes are likely to rupture

Article Title: New method predicts where massive earthquakes will strike

Article References: New method predicts where massive earthquakes will strike. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: earthquakes, subduction zones, GPS geodesy, fault locking, asperities, Kamchatka, tsunami hazard, seismic forecasting, tectonic strain, Hayward Fault, Geophysical Research Letters, disaster preparedness