Deep Time Research Articles

From ONE Health to ONE Paleopathology: Deep-Time Perspectives on Health in the Face of Climate and Environmental Change

This entry explores the emergence of ONE Paleopathology as a holistic, interdisciplinary approach to understanding health through deep time. The entry discusses key areas where paleopathological research provides crucial insights: animals as sentinels of environmental health, the evolution and transmission of infectious diseases, the impacts of urbanization and pollution on human health, and the effects of climate change on disease patterns. Special attention is given to case studies involving malaria, tuberculosis, and environmental toxicity, demonstrating how past human–environment interactions inform current health strategies. The entry also emphasizes the importance of indigenous and local knowledge (ILK) systems in understanding and managing health challenges, highlighting how traditional ecological knowledge complements scientific approaches. By bridging past and present, ONE Paleopathology offers valuable perspectives for addressing modern health challenges in the context of accelerating environmental change, while promoting more equitable and sustainable approaches to global health.

Exploring the utility of unretouched lithic flakes as markers of cultural change

Lithic artefacts provide the principal means to study cultural change in the deep human past. Tools and cores have been the focus of much prior research based on their perceived information content and cultural relevance. Unretouched flakes rarely attract comparable attention in archaeological studies, despite being the most abundant assemblage elements and featuring prominently in ethnographic and experimental work. Here, we examine the potential of flake morphology for tracing cultural change utilising 4,512 flakes, each characterised by 16 standard mixed-scale attributes, from a well-documented cultural sequence at the Middle Stone Age site of Sibhudu, South Africa. We quantified multivariate similarities among flakes using FLEXDIST, a highly versatile method capable of handling mixed, correlated, incomplete, and high-dimensional data. Our findings reveal a significant gradual change in flake morphology that aligns with the documented cultural succession at Sibhudu. Furthermore, our analysis provides new insights into the patterning of variability throughout the studied sequence. The demonstrated potential of flakes to track cultural change opens up additional avenues for comparative research due to their ubiquity, the availability of commonly recorded attributes, and especially in the absence of cores or tools. FLEXDIST, with its versatile applicability to complex lithic datasets, holds particular promise in this regard.

Modeling and Evaluation of Attention Mechanism Neural Network Based on Industrial Time Series Data

Chemical process control systems are complex, and modeling the controlled object is the first task in automatic control and optimal design. Most chemical process modeling experiments require test signals to be applied to the process, which may lead to production interruptions or cause safety accidents. Therefore, this paper proposes an improved transformer model based on a self-attention mechanism for modeling industrial processes. Then, an evaluation mechanism based on root mean square error (RMSE) and Kullback–Leibler divergence (KLD) metrics is designed to obtain more appropriate model parameters. The Variational Auto-Encoder (VAE) network is used to compute the associated KLD. Finally, a real nonlinear dynamic process in the petrochemical industry is modeled and evaluated using the proposed methodology to predict the time series data of the process. This study demonstrates the validity of the proposed transformer model and illustrates the versatility of using an integrated modeling, evaluation, and prediction scheme for nonlinear dynamic processes in process industries. The scheme is of great importance for the field of industrial soft measurements as well as for deep learning-based time series prediction. In addition, the issue of a suitable time domain for the prediction is discussed.

Tropical Glaciation and Glacio-Epochs: Their Tectonic Origin in Paleogeography

Precambrian tropical glaciation is an enigma of Earth’s climate. Overlooking fundamental difference of land/sea icelines, it was equated with a global frozen ocean, which is at odds with the sedimentary evidence of an active hydrological cycle, and its genesis via the runaway ice–albedo feedback conflicts with the mostly ice-free Proterozoic when its trigger threshold was well exceeded by the dimmer sun. In view of these shortfalls, I put forth two key hypotheses of the tropical glaciation: first, if seeded by mountain glaciers, the land ice would advance on sea level to be halted by above-freezing summer temperature, which thus abuts an open cozonal ocean; second, a tropical supercontinent would block the brighter tropical sun to cause the required cooling. To test these hypotheses, I formulate a minimal tropical/polar box model to examine the temperature response to a varying tropical land area and show that tropical glaciation is indeed plausible when the landmass is concentrated in the tropics despite uncertain model parameters. In addition, given the chronology of paleogeography, the model may explain the observed deep time climate to provide a unified account of the faint young Sun paradox, Precambrian tropical glaciations, and Phanerozoic glacio-epochs, reinforcing, therefore, the uniformitarian principle.

Hominin cognition: The null hypothesis.

The target article explores material culture datasets from three African forager groups. After demonstrating that these modern, contemporary human populations would leave scant evidence of symbolic behaviour or material complexity, it cautioned against using material culture as a barometer for human cognition in the deep past. Twenty-one commentaries broadly support or expand these conclusions. A minority offer targeted demurrals, highlighting (1) the soundness of reasoning from absence; and questioning (2) the "cognitively modern" null; (3) the role of hunter-gatherer ethnography; and (4) the pertinence of the inferential issues identified in the target article. In synthesising these discussions, this reply addresses all four points of demurral in turn, and concludes that there is much to be gained from shifting our null assumptions and reconsidering the probabilistic inferential links between past material culture and cognition.

The Memory of the World: Deep Time, Animality, and Eschatology by Ted Toadvine (review)

The Memory of the World: Deep Time, Animality, and Eschatology by Ted Toadvine (review)

Insights into stem Batomorphii: A new holomorphic ray (Chondrichthyes, Elasmobranchii) from the upper Jurassic of Germany.

The Late Jurassic fossil deposits of southern Germany, collectively known as the 'Solnhofen Archipelago', are one of the world's most important sources of Mesozoic vertebrates. Complete skeletons of cartilaginous fishes (Chondrichthyes), whose skeletal remains are rare in the fossil record and therefore all the more valuable, are represented, among others, by exceptionally well-preserved rays (superorder Batomorphii). Despite their potential for research in several areas, including taxonomy, morphology, ecology, and phylogeny, the number of studies on these chondrichthyans is still very limited. Here, we identify a previously unknown ray, †Apolithabatis seioma gen. et sp. nov., which represents the first record of a ray species from the upper Kimmeridgian of Painten, Germany, and thus the oldest Late Jurassic ray taxon from Germany based on skeletal remains. This new batomorph is characterised by a unique body shape and a combination of skeletal features that distinguish it readily from all other known Late Jurassic rays. Two different morphometric approaches confirm differences in body shape and proportions to all known Late Jurassic conspecifics. We thus extend the recent taxonomic revision of these rays and include all described holomorphic specimens in a phylogenetic framework using strict cladistic principles. The phylogenetic analysis reveals all Late Jurassic batomorphs to represent a monophyletic group, for which we introduce the new order Apolithabatiformes, which is sister to all other batomorphs representing a stem group. While the phylogenetic relationships within Apolithabatiformes ord. nov. remain largely unresolved, †Apolithabatis gen. nov. is placed as the sister to †Aellopobatis. This highlights that, despite considerable progress in our understanding of the diversity and phylogeny of early rays, difficulties remain in establishing robust relationships within batomorphs. We therefore emphasise the importance of comprehensive studies of completely preserved fossil cartilaginous fishes to obtain a better understanding of chondrichthyan evolution and their systematics in deep time.

A Model Framework for Scaling Pre‐Quaternary Cosmogenic Nuclide Production Rates

AbstractCosmogenic nuclide dating is an essential component of studying Earth surface processes, but it requires knowledge of how nuclide production rates vary in time and space. Typically, production rates are calibrated at sites with independently well‐constrained exposure histories and then scaled to other sites of interest using scaling frameworks that account for spatial and temporal variations in the secondary cosmic‐ray flux at Earth's surface. To date, scaling schemes for terrestrial cosmogenic nuclide production rates have been developed for the Quaternary, yet cosmogenic nuclide applications that extend beyond the Quaternary are becoming more prevalent. For these deeper time applications, production rate calculations using scaling models optimized for the latest Quaternary neglect longer term spatiotemporal variations in geomagnetic field intensity, paleogeography, and paleoatmospheric depth. We present a production rate scaling scheme for the past 70 million years, SPRITE (Scaling Production Rates In deep TimE). This framework extends existing scaling schemes into deeper time by (a) accounting for site‐specific changes in paleolatitude, (b) integrating a geomagnetic field intensity model rooted in data from a global paleomagnetic database, and (c) incorporating climate‐driven, time‐varying atmospheric depths. We evaluate the efficacy of our model by applying it to existing data sets from paleoexposure sites, and from sites with apparent continuous million‐year exposure histories. This scaling model can be applied with measurements of stable cosmogenic nuclides to research questions such as constraining hiatus durations between ancient lava flows and calculating the formation timescales of stable landforms in arid environments over millions of years.

Dormancy in the origin, evolution and persistence of life on Earth.

Life has existed on Earth for most of the planet's history, yet major gaps and unresolved questions remain about how it first arose and persisted. Early Earth posed numerous challenges for life, including harsh and fluctuating environments. Today, many organisms cope with such conditions by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. This process protects inactive individuals and minimizes the risk of extinction by preserving information that stabilizes life-system dynamics. Here, we develop a framework for understanding dormancy on early Earth, beginning with a primer on dormancy theory and its core criteria. We hypothesize that dormancy-like mechanisms acting on chemical precursors in a prebiotic world may have facilitated the origin of life. Drawing on evidence from phylogenetic reconstructions and the fossil record, we demonstrate that dormancy is prevalent across the tree of life and throughout deep time. These observations lead us to consider how dormancy might have shaped nascent living systems by buffering stochastic processes in small populations, protecting against large-scale planetary disturbances, aiding dispersal in patchy landscapes and facilitating adaptive radiations. Given that dormancy is a fundamental and easily evolved property on Earth, it is also likely to be a feature of life elsewhere in the universe.

Archaeology retains a central role for studying the behavioral and cognitive evolution of our species and genus.

Our species' behavioral and cognitive evolution constitute a key research topic across many scientific disciplines. Based on ethnographic hunter-gatherer data, Stibbard-Hawkes challenges the common link made between past material culture and cognitive capacities. Despite this adequate criticism, archaeology must retain a central role for studying these issues due to its unique access to relevant empirical evidence in deep time.

Re-evaluation of mastodon material from Oregon and Washington, USA, Alberta, Canada, and Hidalgo and Jalisco, Mexico.

The presence of at least two contemporaneous Pleistocene mastodon taxa in North America (Mammut americanum and M. pacificus) invites re-examination of specimens at the geographic margins of each species in order to determine range boundaries, overlaps, and fluctuations. Third molars from Oregon in the United States, as well as from Hidalgo and Jalisco in Mexico, were found to be morphologically consistent with M. pacificus. Washington in the United States includes a number of specimens that could not be confidently assigned to either taxon. Alberta in Canada was found to have some specimens that were consistent with M. pacificus, but others that were identified as M. americanum. The Alberta specimen referred to M. pacificus is the same tooth found to have a Pliocene divergence time from M. americanum based on mitochondrial genome data from a previous study, suggesting a deep divergence time between the two taxa. The apparent presence of both mastodon taxa in close geographic proximity has interesting paleobiogeographic implications. It is not yet clear if both taxa were present simultaneously in a given location; if not, it suggests fluctuating ranges that may reflect shifting climates and/or biomes over time. Alternatively, if both taxa were simultaneously present in the same place, it may suggest a high degree of niche partitioning in mammutids. Additional accurately dated specimens will be required to resolve this question.

DeLVE into Earth's Past: A Visualization-Based Exhibit Deployed Across Multiple Museum Contexts.

While previous work has found success in deploying visualizations as museum exhibits, it has not investigated whether museum context impacts visitor behaviour with these exhibits. We present an interactive Deep-time Literacy Visualization Exhibit (DeLVE) to help museum visitors understand deep time (lengths of extremely long geological processes) by improving proportional reasoning skills through comparison of different time periods. DeLVE uses a new visualization idiom, Connected Multi-Tier Ranges, to visualize curated datasets of past events across multiple scales of time, relating extreme scales with concrete scales that have more familiar magnitudes and units. Museum staff at three separate museums approved the deployment of DeLVE as a digital kiosk, and devoted time to curating a unique dataset in each of them. We collect data from two sources, an observational study and system trace logs. We discuss the importance of context: similar museum exhibits in different contexts were received very differently by visitors. We additionally discuss differences in our process from Sedlmair et al.'s design study methodology which is focused on design studies triggered by connection with collaborators rather than the discovery of a concept to communicate. Supplemental materials are available at: https://osf.io/z53dq/.

A Survey of Time Series Data Forecasting Methods Based on Deep Learning

Time Series Forecasting (TSF) involves predicting future values and trends of data at specific points or periods by analyzing historical patterns, such as trends and seasonality. With the advent of IoT sensors, traditional machine learning approaches struggle to handle massive time series datasets. Recently, deep learning algorithms, exemplified by convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformer models, have made significant progress in time series forecasting tasks. This paper reviews the common features of time series data, relevant datasets, and evaluation metrics for models. It also conducts experimental comparisons of various forecasting algorithms, focusing on time and algorithmic architectures. This paper conducts prediction experiments on several deep learning models using the ETT dataset and presents the final results. We evaluate model performance using metrics like Mean Absolute Error (MAE) and Mean Squared Error (MSE). We highlight the strengths and weaknesses of deep learning-based TSF methods. Major deep learning-based time series forecasting methods are introduced and compared. Finally, challenges and future research directions in applying deep learning to time series forecasting are discussed.

Deep Time, Prehistoric Animals, and the Crystal: J. G. Ballard and Haeckel’s Evolutionary Biology

ABSTRACT This essay reveals British science fiction writer J. G. Ballard’s unknown relationship with German evolutionary biologist Ernst Haeckel (1834–1919), who claimed in the late nineteenth century that ontogenesis was a brief and rapid recapitulation of phylogenesis. Though most of Haeckel’s theories are no longer scientifically influential, Ballard seems to have known a great deal about his extensive work and responded to it in his own “new wave” science fiction by skillfully connecting the recapitulation theory to his exploration of “deep time.” More importantly, Ballard’s concept of “inner space,” which he famously presented in his literary manifesto ”Which Way to Inner Space?” (1962), also seems to be based on Haeckel’s evolutionary biology. To demonstrate this, the paper discusses Haeckel’s direct and indirect influence on Ballard’s novels, such as The Drowned World (1962) and The Crystal World (1966), analyzing the writer’s representations of “deep time,” prehistoric animals, monism, and the crystallization of the world in relation to the theories posited by this forgotten German biologist.

Collaborative Control Strategy of Electric–Thermal–Hydrogen-Integrated Energy System Based on Variable-Frequency Division Coefficient

To address the issues of diverse energy supply demands and power fluctuations in integrated energy systems (IESs), this study takes an IES composed of power-generation units, such as wind and photovoltaic units, along with various energy-storage systems, including electrical, thermal, and hydrogen storage, as the research subject. A collaborative control strategy is proposed for the IES, which comprehensively considers the status of diverse energy-storage systems like battery packs, thermal tanks, and hydrogen tanks. First, a mathematical model of the IES is constructed. Then, a dual-layer collaborative control strategy is designed, considering different operating modes of the IES, which includes a multi-energy-storage power allocation control layer based on second-order power-frequency processing and distribution and an adaptive adjustment layer for adjusting power-frequency coefficients based on adaptive fuzzy control. Finally, MATLAB is used to simulate and validate the proposed strategy. The results indicate that the collaborative control strategy based on variable-frequency coefficients optimizes the allocation of fluctuating power among multiple energy-storage systems, enhances the stability of bus voltage, reduces the deep charge and discharge time of battery packs, and extends the service life of battery packs.

Animal Interface: Digital Design beyond the Humankind

Humankind has always coexisted with other species: its mimetic features and abilities, which include science and art, as well as the graphical user interface that appears at their intersection, express empathy, understanding, premonition, receptivity and adaptation to the complex dynamics of other species, to being among them. At the same time, the interface is considered exclusively as an “anthropological machine,” i.e. as a technical and symbolic representation of the idea of the “absence” of “nature” in man, creating conditions for rupture and isolation with the original factors of mimesis, stirs the need to compensate nature, hypostasis, fantasmatize, stigmatize, etc. — i.e., to think of the experience of nature in terms of a collision with a monster or catastrophe, and to expect salvation from AI, artificial intelligence. Therefore, in order to adequately think through and evaluate interfaces, it is necessary to return to the most “natural” intelligence — mimesis, autopoiesis, biophilia, live communication — it is necessary to give a word to nature, i.e., to take into account the experience of non-human beings, animals, their behavior, communication, dynamics, everything that was considered in the exclusively functional assessment of interfaces rather, “noises,” “interference”. In fact, in order for the interface to express our characteristics, take into account certain aspects of character and behavior, and give us a sense of attention and care, it is necessary that it interact not so much with “pure consciousness” as with our physicality, responding to existential patterns, “deep time” enclosed in our physicality by evolutionary processes, pre-predictive ways of our presence and orientation in reality. We need not only linguistic, neural network, large, etc. data, but also “live” data — for this purpose, the article examines and analyzes the experiences of interaction with animals in interfaces, the features of biophilic information and animalistic design, the participation of animals in the design of interface shells as living environments.

Marine biological responses to abrupt climate change in deep time

Abstract Ancient changes in the biosphere, from organismic traits to wholesale ecosystem changes, can be aligned with climate forcing across the Phanerozoic. Clear examples of abrupt climate warming causing biodiversity crises are primarily found between the Permian and Paleogene periods. During these times, catastrophic events occurred, resembling the extreme climate scenarios projected for the near future. The paleobiologic literature around these events generally supports the hypothesis that abrupt climate change was a dominant trigger of extinction and/or ecological crisis. When climate change and climate history are considered, virtually all post-Paleozoic global biotic events can be confidently attributed to climatic change, with abrupt warming (hyperthermal events) leaving the most consistent fingerprint. The combined stress of deoxygenation and warming are sufficient to explain marine extinction patterns across most hyperthermal events. Although ocean acidification may have contributed, the direct role of pH on the extinction toll of organisms is not consistently demonstrated. Future research can enhance the correspondence between the magnitudes of climatic changes and their biological impacts, even though observed rates of change cannot currently be compared across different timescales. Mimicking multi-scale approaches in modern ecology, paleontological approaches to climate impact research will benefit from specifically targeting scaling relationships.

Reading Deep Time: Contemporary Canadian Geopoetry

ABSTRACT In the collection Strike/Slip (2006), Don McKay, the leading ecopoet in Canada, uses the movement of rocks along a high-angle strike/slip fault to explore the strained but creative relationship between landscape and language, and specifically between geology and ‘poetry as a reader of deep time’. John Terpstra’s poetry also reads the rocks of deep time, particularly in the World Biosphere Reserve of the Niagara Escarpment. Whereas the rock’s hardness has taken 350 million years to form, the people in the city below habitually use hard, divisive language: there needs to be a new Pentecost to ‘change the face/of the earth’ (1997, 45). In exploring several poems from Strike/Slip and from Terpstra’s work, I will consider how geopoetry reads time past, present, and future through encounters with rock, guiding us through astonishment to future possibility.

Digitising the Deep Past: Machine Learning for Rock Art Motif Classification in an Educational Citizen Science Application

Digitising the Deep Past (DDP) is an interdisciplinary project based at Griffith University, Australia, that innovates in three areas: Indigenous cultural heritage, Indigenous education, and Machine Learning (ML) and Artificial Intelligence (AI). The project investigates the use of a purpose-built citizen science application that engages Indigenous youth in educational exercises grounded in local cultural heritage, specifically rock art, making learning more engaging and exposing them to digital technologies. Furthermore, ML models trained with the data gathered through these educational activities can then assist with classifying new rock art images and assisting rangers and archaeologists with site archiving and conservation efforts. This article discusses the project’s significance in enhancing Indigenous science and technology education and outlines its results in using ML for rock art classification. Adopting deep learning in rock art classification offers a compelling avenue for the automated analysis and interpretation of heritage objects and places. However, training deep neural networks from scratch often requires enormous datasets and computational resources, posing challenges for domain-specific applications with smaller datasets. With a dataset comprising approximately 3,100 labeled rock art images, we evaluated various tools within the transfer learning toolbox using three prominent pre-trained architectures: VGG19, ResNet50 and EfficientNet V2 S. Through the collaborative efforts of Indigenous students and ML, we demonstrate that even with limited training resources, using transfer learning to re-purpose an existing model can achieve motif classification Top 1 accuracy of 79.76% and Top 5 of 94.56%. The project ran from 2021 to 2023, including 3 week-long sessions with students of Laura State School to trial the citizen science app and the evaluation, development and refinement of the ML models. The DDP project not only serves as a beacon for community-centric research but also forges a new frontier in integrating Indigenous cultural heritage with modern technology. The impact reaches beyond academia, directly enriching the educational experience for Indigenous students in Laura and equipping local rangers and archaeologists with advanced tools for rock art conservation.

The evolution and genetic basis of a functionally critical skull bone, the parasphenoid, among Lake Malawi cichlids.

Adaptive radiation, whereby a clade pairs rapid speciation with rapid phenotypic evolution, can result in an uneven distribution of biodiversity across the Metazoan tree. The cichlid fishes of East Africa have undergone multiple adaptive radiations within the major rift lakes. Cichlid radiations are marked by divergence across distinct habitat gradients producing many morphological and behavioural adaptations. Here, we characterize the shape of the parasphenoid, a bone in the neurocranium that dissipates forces generated during feeding. We examine Tropheops, a group that has transitioned between deep and shallow habitats multiple times, to examine habitat-specific differences in parasphenoid shape. We find differences in the depth and length of the parasphenoid between Tropheops residing in each habitat, variation that may impact the ability of the cranium to resist force. We next use a hybrid cross between two cichlid species that differ in parasphenoid shape, Labeotropheus and Tropheops, to examine the genetic basis of these morphological differences. We perform genetic mapping and identify two genomic regions responsible for variation in parasphenoid shape. These regions are implicated in other functional traits including the oral jaws and neurocranium, indicating that the genetic landscape for adaptive evolution may be limited to a few loci with broad effects. Repurposing the same gene(s) for multiple traits via regulatory evolution may be sufficient for selection to drive transitions between habitats important for incipient stages of adaptive radiations.