State of the Art in Paleoenvironment Mapping for Modeling Applications in Archeology—Summary, Conclusions, and Future Directions from the PaleoMaps Workshop

Abstract

In this report, we present the contributions, outcomes, ideas, discussions and conclusions obtained at the PaleoMaps Workshop 2019, that took place at the Institute of Geography of the University of Cologne on 23 and 24 September 2019. The twofold aim of the workshop was: (1) to provide an overview of approaches and methods that are presently used to incorporate paleoenvironmental information in human–environment interaction modeling applications, and building thereon; (2) to devise new approaches and solutions that might be used to enhance the reconstruction of past human–environmental interconnections. This report first outlines the presented papers, and then provides a joint protocol of the often extensive discussions that came up following the presentations or else during the refreshment intervals. It concludes by adressing the open points to be resolved in future research avenues, e.g., implementation of open science practices, new procedures for reviewing of publications, and future concepts for quality assurance of the often complex paleoenvironmental data. This report may serve as an overview of the state of the art in paleoenvironment mapping and modeling. It includes an extensive compilation of the basic literature, as provided by the workshop attendants, which will itself facilitate the necessary future research.

The ROCEEH Out of Africa Database (ROAD): A large-scale research database serves as an indispensable tool for human evolutionary studies

“…Second, it enables us to study human evolution through a geographic perspective by examining the expansion of early humans through different lenses, for example: the shape of landmasses [38], climatic effects on human habitats [39,40] and human bodies [41], or the susceptibility of expansion routes [42][43][44]. New insights can be gained when ROAD's point data, which cover the where, what and when, are integrated with the growing amount of spatially and temporally continuous datasets about the past [45,46], including climate models [47,48], vegetation reconstructions [49] and glacial extents [50]. Therefore, ROAD represents a valuable source of data for classical spatial analysis and modeling, spatial network analysis, agent based modeling, ecological niche modeling, spatial diffusion modeling and the growing number of methods fueled by geospatial machine learning and artificial intelligence.…”

Approaching prehistoric demography: proxies, scales and scope of the Cologne Protocol in European contexts

“…This makes areal estimation more conservative than approaches considering all single archaeological occurrences with covering hulls (see the electronic supplementary material, S1.1 and 1.4). It is also less prone to distortions by new discoveries, and therefore, results are considered more robust [ 32 ]. The approach assumes, firstly, that the distribution of sites across the landscape reflects human occupation during a defined period; secondly, that biases thereof can be identified or controlled through critical evaluation of equivalent data from preceding and succeeding periods in the same region; and thirdly, that a certain level of site density will reflect Core Areas of intense and continuous occupation.…”

River flood reconstruction in the Lower Rhine valley and delta

“…The need for palaeo-DEMs is widespread across geomorphological studies focusing on reconstruction or modelling, on both short (<10 3 yr) and longer (>10 3 yr) time scales, and at a variety of spatial scales. At a regional scale, palaeo-DEMs help to understand the historical and geomorphological evolution of an area (Werbrouck et al, 2011;Vermeer et al, 2014;Pierik et al, 2017;Briant et al, 2018;Pierik and van Lanen, 2019), and aid in landscape-archaeological regional inventories and archaeological modelling van Lanen et al, 2018;van Lanen and Pierik, 2019;Willmes et al, 2020). At a local scale, palaeo-DEMs are key to identify past natural and artificial drainage network elements (Baubiniene et al, 2015;Kirchner et al, 2017;Schmidt et al, 2018), and to map the geomorphological contexts of early settlements and urban centres (Schneider et al, 2017;Mozzi et al, 2018;Grimm and Heinrich, 2019;Pröschel and Lehmkuhl, 2019).…”