Crawford Lake owes its extraordinary preservative powers to an unusual physical quirk. It is a meromictic lake, meaning its water column never fully mixes with the lakebed. Because the deep waters remain undisturbed, sediment settling from the surface is laid down in neat, alternating layers of calcite and organic-rich laminae, each pair representing a single year of deposition. Matthew Emery, co-first author of the study and assistant professor of anthropology at Binghamton University, compared the structure to the growth rings of a tree. Like those rings, each sediment layer can be dated to a specific year, offering an exceptionally well-preserved, year-by-year account of environmental change. That annual resolution, combined with the lake’s status as one of the most intensively studied lakes in the world, gave the sedaDNA team an unparalleled opportunity to test their methods against decades of established palaeoecological evidence.

The technique at the heart of the study descends from methods originally developed to hunt far older quarry. Researchers used capture enrichment, a process in which genetic baits made of RNA are designed to bind to the DNA of target species if those genetic fragments are present in a sample. The RNA baits also attach to magnetic beads, allowing scientists to literally reel in their target DNA with a magnet. Emery noted that these approaches were first engineered to chase down extinct Pleistocene megafauna and extinct hominin relatives such as Neanderthals and Denisovans. Now, they are being applied to lake mud to trace human-environment interactions spanning recent centuries and reaching deep into geological time. Bait sets can be combined to target hundreds or even thousands of species genomes simultaneously, making the approach far more efficient than random shotgun sequencing, and allowing researchers to choose in advance which organisms they want to search for in the archive.

The reconstructed timeline traces a dramatic arc of human influence. In the period before local agriculture, the sedaDNA records a landscape shaped only by natural processes. Between the 1200s and the 1500s, the genetic evidence confirms the presence of Indigenous peoples farming maize and sunflowers near the lake, a finding that aligns with archaeological evidence of Longhouse Peoples villages at the site. The data also captures site abandonment and the ecological succession that followed, and then documents the Euro-Canadian period, with renewed impacts from logging, lumbering, milling, and farming, culminating in the unmistakable global markers of industrialization in the upper layers, including fossil fuel remnants, plastics, artificial fertilizers, acid rain, and even plutonium. It was precisely this well-preserved contamination record that made Crawford Lake a leading candidate among geologists supporting the Anthropocene as a new geological epoch, a designation that was ultimately rejected even as the scientific debate continues.

Among the study’s most striking results is the recovery of genetic evidence invisible to traditional palaeoecological techniques. Cattle DNA appears in sediments dating to the early 1800s, providing new proof of cattle in the surrounding landscape that left no trace in the fossil or pollen record. Even more remarkably, the analysis detected two of the so-called Four Sisters crops, maize and sunflower, directly from lake core samples for the first time. Three Sisters agriculture is an Indigenous farming technique introduced to the Great Lakes region during the Late Woodland Period, roughly 1000 to 1650 CE, in which maize, beans, and squash are planted side by side in mutually beneficial combinations. When sunflower is added, the grouping becomes the Four Sisters. While fossil and pollen studies had previously confirmed beans and squash at the Crawford Lake village site, those two crops were absent from the lake sediments, a puzzle the researchers attribute to the dietary preferences of an unexpected intermediary.

That intermediary is the Canada goose. The sedaDNA record shows a sharp increase in Canada goose DNA during the periods of Indigenous agriculture, a pattern consistent with geese foraging in cultivated maize and sunflower fields and then roosting on Crawford Lake. Their droppings would have carried both nutrients and traces of the crops they had eaten into the water, likely driving repeated algal blooms from nutrient influxes that are also visible in the sedimentary genetic record. These eutrophication events, caused by excess nutrients in the water, may even have contributed to the abandonment of the site, which occurred on more than one occasion according to the timeline. After abandonment in the 1500s, the lake’s ecology gradually rebounded, with the record showing a return of pine trees, rabbits, deer, beavers, and loons, and a notable disappearance of maize. Today, similar blooms are more often driven by artificial fertilizers, but the Crawford Lake record shows that nutrient-driven algal booms have deep human roots.

The study also delivered surprises about the physics of DNA decay itself. One of the biggest revelations, according to co-first author Tyler Murchie, lead scientist of Biodiversity Genomics: Ancient DNA at the Hakai Institute and adjunct assistant professor of anthropology at McMaster University, is that older DNA is not necessarily more damaged. Some of the roughly 500-year-old lake sedaDNA from plants and animals at Crawford Lake proved more degraded than DNA tens to hundreds of thousands of years old recovered from permafrost sites in northwestern Canada, demonstrating that preservation conditions matter far more than age alone. The chemistry of a burial environment, whether frozen, waterlogged, mineral-rich, or oxygenated, can determine whether genetic fragments survive intact for millennia or crumble into unreadable noise within a few centuries. For a small lake in southern Ontario, the cold, still, stratified water column turned out to be an unexpectedly generous custodian of molecular history.

The research was not without technical limitations, and the team has been candid about them. The bait set used in the analysis, the PaleoChip Arctic v1.0, was designed for Pleistocene and early Holocene sites far older than the period of human activity at Crawford Lake, and the absence of beans and squash in the results may reflect a gap in that panel or the geese’s preference for maize and sunflower. The researchers are already working to improve their bait sets for better capture enrichment, with Murchie emphasizing the need for an Eastern Woodland panel for future targeted ancient DNA research in the region. The effort has momentum behind it: in January, co-senior author Hendrik Poinar, professor of anthropology at McMaster University, and Murchie received an NSERC Alliance grant to develop improved sedaDNA methods for permafrost and marine sediments, support the reconstruction of long-term terrestrial and marine ecosystem dynamics, and build the Canadian Ancient DNA Network.

Beyond its technical achievements, the study underscores the collaborative nature of modern environmental science. Poinar noted that the work was only possible through the combination of genetics, archaeology, traditional Indigenous knowledge, lake chemistry, and geochemistry, disciplines that together make the unknown a little more tangible and the past recoverable, almost like magic. The international team included scientists from McMaster University, the Hakai Institute, Brock University, the University of Alberta, and the University of British Columbia in Canada; Binghamton University and Arizona State University in the United States; and Stockholm University in Sweden. Emery described the layered sediment as a filing cabinet and a time capsule, each stratum holding the plants and animals that lived around the lake when it formed, readable straight down through the centuries as long as nothing has shuffled the order. As the debate over the Anthropocene continues, Crawford Lake’s genetic archive now offers a thousand-year benchmark against which humanity’s accelerating transformation of the natural world can be measured, one annual layer at a time.

Subject of Research: Sedimentary ancient DNA analysis reconstructing 1,000 years of human-environment interactions at Crawford Lake, Ontario

Article Title: Ancient DNA reveals 1,000 years of human–environment interactions at Crawford Lake

Article References: Ancient DNA reveals 1,000 years of human–environment interactions at Crawford Lake. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: ancient DNA, sedaDNA, Crawford Lake, Anthropocene, Indigenous agriculture, Three Sisters, eutrophication, capture enrichment, molecular ecology, palaeoecology, meromictic lake, environmental change

The review, authored by Camille A. Troisi of the Centre d’Étude en Éthologie et Cognition at the Université de Rennes in France, takes a deliberately analytical approach to the problem. Rather than treating social learning as a single, indivisible behaviour, Troisi separates it into two conceptual components: the social component, which concerns the availability and use of information produced by other individuals, and the learning component, which concerns the cognitive machinery that converts observed or transmitted information into lasting behavioural change. This distinction matters because urban factors may act on each component in different, and sometimes opposing, ways.

Social learning is widely predicted to be most useful in novel or variable environments. When an animal faces a new food source, a new predator or a new hazard, copying an experienced individual can be far cheaper and safer than trial-and-error exploration. Urban environments, with their rapid change and abundance of unfamiliar challenges, appear tailor-made for this strategy. Yet, as the review emphasises, whether animals actually rely on social information in cities depends on a chain of conditions: the information must be available, it must be genuinely useful, individuals must be inclined to use it, and they must be capable of learning from it. Disruption at any link in this chain can weaken the whole process.

Pollution emerges as one of the most pervasive urban factors with the potential to interfere with social learning, and Troisi examines it in three distinct forms. Chemical pollution, including heavy metals and endocrine-disrupting compounds, can impair cognition directly, degrading the attention, memory and sensory processing needed to detect and interpret social cues. Noise pollution poses a different problem: acoustic signals are among the most important channels of social information for birds, mammals and other vocal species, and chronic urban noise can mask calls and songs, effectively cutting the bandwidth through which social information flows. Light pollution adds a further layer, altering activity patterns and potentially desynchronising the timing of social interactions between individuals that would otherwise learn from one another.

Food resources represent another pathway with ambiguous consequences. Cities often provide abundant, predictable and clumped food sources, from rubbish bins to bird feeders. On the one hand, such predictability might reduce the need for social learning, since individuals can locate resources through simple routines rather than by following others. On the other hand, concentrated food can increase the frequency of social interactions and produce local traditions, as has been observed in urban birds and mammals that learn novel foraging techniques from conspecifics. The review highlights that the direction of the effect likely depends on how resources are distributed in space and time, and on how competition shapes the willingness of individuals to allow others close enough to be observed.

Temperature is a factor that is easy to overlook but potentially significant. Urban heat islands raise ambient temperatures relative to surrounding rural areas, and temperature influences metabolic rate, activity levels and the timing of behaviour. Because social learning depends on temporal overlap between demonstrators and observers, thermal shifts that alter daily activity patterns could change who meets whom, and when. Warmer nights, for example, may extend or shift activity windows, potentially increasing opportunities for social contact for some species while reducing them for others.

Habitat structure plays an equally complex role. The built environment alters sightlines, creates vertical structures and fragments vegetation, all of which influence how easily animals can observe one another. Dense buildings may block visual transmission of social information, while at the same time creating new vantage points such as ledges, wires and rooftops where animals congregate visibly. Furthermore, structural features of cities can change the value of what is learned: navigating a maze of glass and asphalt may demand entirely new route knowledge, and experienced residents may hold information about safe corridors and hazards that naive individuals cannot easily acquire alone.

Perhaps the most distinctive feature of urban environments is the sheer pace of environmental change. Social learning carries an inherent risk: information can become outdated. In rapidly changing environments, information copied from others may be obsolete by the time it is used, favouring asocial, individual learning instead. Troisi points out that this dynamic could cut against the intuitive prediction that cities should promote social learning. If the urban landscape, traffic patterns or human behaviours that generate rewards and risks change faster than social information can circulate, animals may do better by sampling the environment themselves. The usefulness of social information, in other words, is not a fixed property but a moving target shaped by the rate of change.

Across all of these factors, the review reaches a sobering conclusion. Although there are substantial bodies of research on each individual component — on how pollution affects cognition, on how noise alters communication, on how animals learn socially in laboratory and wild settings — very little empirical work directly examines the relationship between urbanisation and social learning as an integrated whole. Most conclusions about urban social learning are therefore extrapolations rather than demonstrations. The review serves as both a synthesis of what is plausibly known and a roadmap for what remains to be tested, identifying where the logical pathways from urban factors to social information use are strongest and where empirical data are thinnest.

The implications extend beyond academic curiosity. Understanding how animals adapt cognitively to cities is increasingly relevant to conservation, urban planning and the management of human-wildlife conflict. Species that exploit social information effectively may be better equipped to colonise and thrive in urban areas, potentially explaining why some species flourish alongside humans while others retreat. If pollution, noise or the pace of change erode social learning in vulnerable species, cities could be imposing hidden cognitive costs that compound more visible threats. Filling the empirical gap that this review exposes will require targeted experiments comparing social learning performance across urban and rural populations, across gradients of urbanisation, and under controlled manipulations of the specific factors the review identifies. Until such studies accumulate, the question of whether city life makes animals more — or less — reliant on the wisdom of others remains one of behavioural ecology’s compelling open problems.

Subject of Research: The factors in urban environments that influence animals' reliance on and the usefulness of social learning.

Article Title: Factors impacting reliance on, and usefulness of, social learning in urban environments

Article References: Troisi, C. A. (2026). Factors impacting reliance on, and usefulness of, social learning in urban environments. Animal Cognition. https://doi.org/10.1007/s10071-026-02100-1

Image Credits: AI Generated

DOI: 10.1007/s10071-026-02100-1

Keywords: social learning, urbanisation, animal cognition, urban ecology, noise pollution, chemical pollution, light pollution, food resources, habitat structure, environmental change, behavioural ecology, animal behaviour