Various biological systems have been subjected to mathematical modelling to enhance our understanding of the intricate interactions among different species. Among these models, the predator-prey model holds a significant position. Its relevance stems not only from its application in biology, where it largely governs the coexistence of diverse species in open ecosystems, but also from its utility in other domains. 

Predator-prey dynamics have long been a focal point in population ecology, yet access to real-world data is confined to relatively brief periods, typically less than a century. Studying predator-prey dynamics over extended periods presents challenges due to the limited availability of population data spanning more than a century. The most extensive dataset is the hare-lynx records from the Hudson Bay Company, documenting a century of fur trade [1]. However, other records are considerably shorter, usually spanning decades [2,3]. This constraint hampers our capacity to investigate predator-prey interactions over centennial or millennial scales. 

Marom and Wolkowski [4] propose here that leveraging regional radiocarbon databases offers a solution to this challenge, enabling the reconstruction of predator-prey population dynamics over extensive timeframes. To substantiate this proposition, they draw upon examples from Pleistocene Beringia and the Holocene Judean Desert. This approach is highly relevant and might provide insight into ecological processes occurring at a time scale beyond the limits of current ecological datasets. 

The methodological approach employed in this article proposes that the summed probability distribution (SPD) of predator radiocarbon dates, which reflects changes in population size, will demonstrate either more or less variation than anticipated from random sampling in a homogeneous distribution spanning the same timeframe. A deviation from randomness would imply a covariation between predator and prey populations. This basic hypothesis makes no assumptions about the frequency, mechanism, or cause of predator-prey interactions, as it is assumed that such aspects cannot be adequately tested with the available data. If validated, this hypothesis would offer initial support for the idea that long-term regional radiocarbon data contain signals of predator-prey interactions. This approach could justify the construction of larger datasets to facilitate a more comprehensive exploration of these signal structures.

References

[1] Elton, C. and Nicholson, M., 1942. The Ten-Year Cycle in Numbers of the Lynx in Canada. J. Anim. Ecol. 11, 215–244.

[2] Gilg, O., Sittler, B. and Hanski, I., 2009. Climate change and cyclic predator-prey population dynamics in the high Arctic. Glob. Chang. Biol. 15, 2634–2652. https://doi.org/10.1111/j.1365-2486.2009.01927.x

[3] Vucetich, J.A., Hebblewhite, M., Smith, D.W. and Peterson, R.O., 2011. Predicting prey population dynamics from kill rate, predation rate and predator-prey ratios in three wolf-ungulate systems. J. Anim. Ecol. 80, 1236–1245. https://doi.org/10.1111/j.1365-2656.2011.01855.x

[4] Marom, N. and Wolkowski, U. (2024). A note on predator-prey dynamics in radiocarbon datasets, BioRxiv, 566733, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.1101/2023.11.12.566733

The archaeological record comes in many forms. Some, such as buried sites from volcanic eruptions or other abrupt sedimentary phenomena are perhaps the only ones that leave relatively clean snapshots of moments in the past. And even in those cases time is compressed. Much, if not all other archaeological record is a messy affair. Things, whatever those things may be, artifacts or construction works (i.e., features), moved, modified, destroyed, warped and in a myriad of ways modified from their behavioral contexts. Do we at some point say the record is worthless? Not worth the effort or continuing investigation. Perhaps sometimes this may be justified, but as Daffara and colleagues show, heavily impacted archaeological remains can give us clues and important information about the past. Thoughtful and careful prehistorians can make significant contributions from what appear to be poor archaeological records. 

            In the case of Daffara and colleagues, a number of important theoretical cross-sections can be recognized. For a long time surface archaeology was thought of simply as a way of getting a preliminary peak at the subsurface. From some of the earliest professional archaeologists (e.g., Kidder 1924, 1931; Nelson 1916) to the New Archaeologists of the 1960s, the link between the surface and subsurface was only improved in precision and systematization (Binford et al. 1970). However, at Hatchery West Binford and colleagues not only showed that surface material can be used more reliably to get at the subsurface, but that substantive behavioral inferences can be made with the archaeological record visible on the surface.

            Much more important are the behavioral implications drawn from surface material. I am not sure we can cite the first attempts at interpreting prehistory from the surface manifestations of the archaeological record, but a flurry of such approaches proliferated in the 1970s and beyond (Dunnell and Dancey 1983; Ebert 1992; Foley 1981).  Off-site archaeology, non-site archaeology, later morphing into landscape archaeology all deal strictly with surface archaeological record to aid in understanding the past. With the current paper, Daffara and colleagues (2024) are clearly in this camp. Although still not widely accepted, it is clear that some behaviors (parts of systems) can only be approached from surface archaeological record. It is very unlikely that a future archaeologist will be able to excavate an entire human social/cultural system; people moving from season to season, creating multiple long and short term camps, travelling, procuring resources, etc. To excavate an entire system one would need to excavate 20,000 km2 or some similarly impossible task. Even if it was physically possible to excavate such an enormous area, it is very likely that some of contextual elements of any such system will be surface manifestations. 

Without belaboring the point, surface archaeological record yields data like any other archaeological record. We must contextual the archaeological artifacts or features weather they come from surface or below. Daffara and colleagues show us that we can learn about deep prehistory of northern Italy, with collections that were unsystematically collected, biased by agricultural as well as other land deformations agents. They carefully describe the regional prehistory as we know it, in particular specific well documented sites and assemblages as a means of applying such knowledge to less well controlled or uncontrolled collections.

References

Binford, L., Binford, R. S. R., Whallon, R. and Hardin, M. A. (1970). Archaeology of Hatchery West. Memoirs of the Society for American Archaeology, No. 24, Washington D.C.

Daffara, S., Giraudi, C., Berruti, G. L. F., Caracausi, S. and Garanzini, F. (2024). First evidence of a Palaeolithic frequentation of the Po plain in Piedmont: the case of Trino (north-western Italy), OSF Preprints, pz4uf, ver. 6 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.31219/osf.io/pz4uf

Dunnell, R. C. and Dancey, W. S. (1983). The siteless survey: a regional scale data collection strategy. In Advances in Archaeological Method and Theory, vol. 6, edited by Michael B. Schiffer, pp. 267-287. Academic Press, New York.

Ebert, J. I. (1992). Distributional Archaeology. University of New Mexico Press, Albuquerque.

Foley, R. A. (1981). Off site archaeology and human adaptation in eastern Africa: An analysis of regional artefact density in the Amboseli, Southern Kenya. British Archaeological Reports International Series 97. Cambridge Monographs in African Archaeology 3. Oxford England.

Kidder, A. V. (1924). An Introduction to the Study of Southwestern Archaeology, With a Preliminary Account of the Excavations at Pecos. Papers of the Southwestern Expedition, Phillips Academy, no. 1. New Haven, Connecticut.

Kidder, A. V. (1931). The Pottery of Pecos, vol. 1. Papers of the Southwestern Expedition, Phillips Academy. New Haven, Connecticut.

Nelson, N. (1916). Chronology of the Tano Ruins, New Mexico. American Anthropologist 18(2):159-180.

The paper entitled “Comparing summed probability distributions of shoreline and radiocarbon dates from the Mesolithic Skagerrak coast of Norway” by Isak Roalkvam and Steinar Solheim (2024) sheds new light on the degree to which shoreline dating may be used as a reliable chronological and palaeodemographic proxy in the Mesolthic of southern Norway.

Based on geologically motivated investigations of eustatic and isostatic sea-level changes, shoreline dating has long been used as a method to date archaeological sites in Scandinavia, not least in Norway (e.g., Bjerck 2008; Astrup 2018). Establishing reliable sea-level curves requires much effort and variations across regions may be substantial. While this topic has seen a great deal of attention in Norway specifically, many purely geological questions remain. In addition, dating archaeological sites by linking their elevation to previously established seal-level curves relies strongly on the foundational assumption that such sites were in fact shore-bound. Given the strong contrast between terrestrial and marine productivity in high-latitude regions such as Norway, this assumption per se is not unreasonable. It is very likely that the sea has played a decisive role in the lives of Stone Age peoples throughout (Persson et al. 2017), just as it has in later periods here. However, many confounding factors relating to both taphonomy and human behaviour are also likely to have loosened the shore/site relationship. Systematic variations driven by cultural norms about settlement location, mobility, as well as factors such as shelter construction, fuel use and a range of other possible factors could variously have impacted the validity or at least the precision of shoreline dating.

By developing a new methodology for handling and assessing a large number of shoreline dated sites, Roalkvam and Solheim use state-of-the-art Bayesian statistical methods to compare shoreline and radiocarbon dates as proxies for population activity. The probabilistic treatment of shoreline dates in this way is novel, and the divergences between the two data sets are interpreted by the authors in light of specific behavioural, cultural, and demographic changes. Many of the peaks and troughs observed in these time-series may be interpreted in light of long-observed cultural transitions while others may relate to population dynamics now also visible in palaeogenomic analyses (Günther et al. 2018; Manninen et al. 2021). Overall, this paper makes an innovative and fresh contribution to the use of shoreline dating in Norwegian archaeology, specifically by articulating it with recent developments in Open Science and data-driven approaches to archaeological questions (Marwick et al. 2017).

References

Astrup, P. M. 2018. Sea-Level Change in Mesolithic Southern Scandinavia : Long- and Short-Term Effects on Society and the Environment. Aarhus: Aarhus University Press.

Bjerck, H. B. 2008. Norwegian Mesolithic Trends: A Review. In Mesolithic Europe, edited by Geoff Bailey and Penny Spikins, 60–106. Cambridge: Cambridge University Press.

Günther, T., Malmström, H., Svensson, E. M., Omrak, A., Sánchez-Quinto, F., Kılınç, G. M., Krzewińska, M. et al. 2018. Population Genomics of Mesolithic Scandinavia: Investigating Early Postglacial Migration Routes and High-Latitude Adaptation. PLOS Biology 16 (1): e2003703. https://doi.org/10.1371/journal.pbio.2003703

Manninen, M. A., Damlien, H., Kleppe, J. I., Knutsson, K., Murashkin, A., Niemi, A. R., Rosenvinge, C. S. and Persson, P. 2021. First Encounters in the North: Cultural Diversity and Gene Flow in Early Mesolithic Scandinavia. Antiquity 95 (380): 310–28. https://doi.org/10.15184/aqy.2020.252

Marwick, B., d’Alpoim Guedes, J. A., Barton, C. M., Bates, L. A., Baxter, M., Bevan, A., Bollwerk, E. A. et al. 2017. Open Science in Archaeology. The SAA Archaeological Record 17 (4): 8–14. https://doi.org/10.31235/osf.io/72n8g

Persson, P., Riede, F., Skar, B., Breivik, H. M. and Jonsson, L. 2017. The Ecology of Early Settlement in Northern Europe: Conditions for Subsistence and Survival. Sheffield: Equinox.

Roalkvam, I. and Solheim, S. (2024). Comparing summed probability distributions of shoreline and radiocarbon dates from the Mesolithic Skagerrak coast of Norway, SocArXiv, 2f8ph, ver. 5 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.31235/osf.io/2f8ph

In this paper (Linsel/Bullenkamp/Mara 2024), the authors propose an automatic system for scar-ridge-pattern detection on palaeolithic artefacts based on Morse Theory. Scare-Ridge pattern recognition is a process that is usually done manually while creating a drawing of the object itself. Automatic systems to detect scars or ridges exist, but only a small amount of them is utilizing 3D data. In addition to the scar-ridges detection, the authors also experiment in automatically detecting the operational sequence, the temporal relation between scars and ridges. As a result, they can export a traditional drawing as well as graph models displaying the relationships between the scars and ridges.

After an introduction to the project and the practice of documenting palaeolithic artefacts, the authors explain their procedure in automatising the analysis of scars and ridges as well as their temporal relation to each other on these artefacts. To illustrate the process, an open dataset of lithic artefacts from the Grotta di Fumane, Italy, was used and 62 artefacts selected. To establish a Ground Truth, the artefacts were first annotated manually. The authors then continue to explain in detail each step of the automated process that follows and the results obtained.

In the second part of the paper, the results are presented. First the results of the segmentation process shows that the average percentage of correctly labelled vertices is over 91%, which is a remarkable result. The graph modelling however shows some more difficulties, which the authors are aware of. To enhance the process, the authors rightfully aim to include datasets of experimental archaeology in the future. They also aim to develop a way of detecting the operational sequence automatically and precisely.

This paper has great potential as it showcases exactly what Digital and Computational Archaeology is about: The development of new digital methods to enhance the analysis of archaeological data. While this procedure is still in development, the authors were able to present a valuable contribution to the automatization of analytical archaeology. By creating a step towards the machine-readability of this data, they also open up the way to further steps in machine learning within Archaeology.

Bibliography

Linsel, F., Bullenkamp, J. P., and Mara, H. (2024). Linking Scars: Topology-based Scar Detection and Graph Modeling of Paleolithic Artifacts in 3D, Zenodo, 8296269, ver. 3 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8296269

The paper by A. Lien-Talks [1] presents a small project looking at the use of crowd sourced data collection and particpatory GIS. In particular it looks at the potential of these tools in response to socially disruptive and isolating events such as the COVID-19 pandemic as well as the potential role of digitially mediated heritage initiatives in tackling some of the challenges of changing demographics and life styles.

The types of technologies employed are relatively mature, the project identifies potential for such approaches to be used within the local-history/local community settings, though is also a reminer that depsite the much broader adoption of technology within all areas of society than even a few years ago many barriers still remain. While the the sample size and data collected in the project is relatively modest, the focus on empathy toward the intended audiences from the design process, as well as some of the qualitative feedback reported serve as a reminder that participatory, or crowd-sourced data collection initiatives in heritage can, and perhaps should place potential social benefit before data-acquisition of objectives.

The project also presents a demographic that is not often represented within the literature and the publication and as such the publication of the article represents a meaningful contribution to ongoing discussions of the role heritage and digitally mediated community archaeology can play a role in developing our societies.

References

[1] Lien-Talks, A. (2024). The Ashwell Project: Creating an Online Geospatial Community. Zenodo, 8307882, ver. 4 peer-reviewed and recommended by Peer Community in Archaeology. https://doi.org/10.5281/zenodo.8307882