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PEOPLE 3000 scientific goals

Phase 2 of the PEOPLE 3000 working group has three overarching goals:

1.  Integrate paleoecological, paleoclimate, and paleo data on social integration with paleo-population data

Our working group builds on 17 core case studies represented by key members of our WG. These case studies all have abundant archaeological radiocarbon or other datasets useful for reconstructing past population dynamics. In each case study, we are synthesizing paleoenvironmental records to identify periods of change in disturbance regime variability (both from high to low variability and low to high variability) at multiple scales. For instance, the development of end-to-end Bayesian demographic reconstruction (Price et al. 2021) allows for the integration of many types of data within paleo-population reconstructions. House/room counts, skeletal age-at-death, pottery amount, or other social data may offer additional lines of evidence for demography that, together with radiocarbon, begin to converge towards a useful estimate of the distribution of past populations and compare those paleo-population reconstructions with vegetation and paleoclimate data.

We will identify disturbance regimes in each case study area by synthesizing paleoecological data within each region from open sources, publications, and our expert knowledge (e.g. NEOTOMA, Kaufman et al. 2020; Zhao et al. 2019; Grissino-Mayer et al. 1997). Once we synthesize the time-series, we will conduct regime shift and wavelet analysis in order to determine significant changes in the frequency and scale of paleoclimate variability in each region (e.g. Finley et al. 2019; Donges et al. 2015; Prokoph and Bilali 2008). We anticipate conducting this activity at workshop #1 in phase two of the working group. Describing changes in variability is critical for our group’s research, and we will push methodological boundaries through Bayesian analysis of existing records, building on regime shift detection where chronological models warrant (Zou et al. 2019; Donges et al. 2015), and coarser grained analyses where chronological models are less precise. Significant changes in a time-series will define different disturbance regime windows experienced by SES at decadal and centennial scales, and we will match these windows to changes in population time-series. Finally, we anticipate that our data construction will prove useful for assessing types of ecosystems modifications following changes in disturbance regimes following methodologies developed by Nolan et al. (2018).

We will divide time-series into disturbance regime variability windows and synthesize archaeological data to compare between these windows. We will compare estimates of social integration and violence in our case studies. We will create time-series of these measures and estimate the degree of change (if any) following a change in disturbance regime variability and the time to recovery. Collating these records will be the topic of Workshop #2 in phase two of our working group. To estimate the level of social integration, we will use existing sources to document the presence of communal architecture, the size of public space associated with such architecture, and the frequency of violence associated with burials. The first two classes of data are widely available and provide a powerful measure because such architecture is closely tied to economic complexity and more encompassing social-political institutions that integrate larger populations (e.g., McCurdy 2019, Turchin et al. 2018; Hegmon et al. 2008). We will document the presence and absence of monumental architectures and frequencies of violence/warfare (where available) from time t to time t+1. We will document whether communal architecture increases, decreases, or remains unchanged following a shift in disturbance regime. If there is a change, we will document whether the system ever moves back to its previous state of communal architecture

2. Expand case studies and integrate global paleo-population proxies with existing, global scale paleoecological/climatological datasets

In conjunction with goal #1, we will begin the process of integrating global archaeological data with global paleoecological and plaeoclimatological data. This will occur during workshops #1 and #2 as we attempt to expand our core case studies. We have established collaborations with other PAGES working groups as well as other initiatives to develop synergies and integrate data. For instance, we will draw on the work of the PAGES 2K WG to integrate data on changes in climate means and variability over the last 2000 years with paleo-population records. Throughout established connections with the HOPE, CLaSS, and NEOTOMA projects, we will integrate proxy-data for changes in vegetation and human impacts on different biomes over the Holocene. Specifically, HOPE has developed a global pollen database similar in scope to the PEOPLE 3000 published radiocarbon database. We have established working relationships (key P3K member Suzette Flantua, e.g., Felde et al. 2020) with the HOPE project, and we will integrate these databases in phase two of the project to identify potential correlated changes in vegetation and human population. CLaSS includes climate modelling, the construction of ADEMNES 2.0 to support vegetation reconstruction, and a large settlement database of over 100,000 sites for SW Asia. Together these datasets allow for detecting changes in vegetation, assessment of human impact, etc. from 8000 to 2000 BP, and we have established contact with CLaSS to integrate our datasets (key P3K member Michelle de Gruchy, e.g., de Gruchy et al 2016).

3. Identify SES coevolutionary trajectories (or lack thereof) as a foundation for understanding the general resilience of SES to changes in disturbance regimes

This final goal sets the stage for synthesis during phase three of our proposed working group and will be the focus of workshop #3 in phase two. As discussed above, we will use the simple logistic model as a foundation of comparison across our case studies. This model is attractive as a starting point because of its simplicity. However, the whole point of this goal is to quantitatively assess the interrelationships between changes in human population proxies, social integration, and paleoecological time series before and after changes in the variability of temperature and rainfall. To this end, we will draw on our group’s interdisciplinary composition to explore formal models and statistical approaches. 

Completing our goals during phase two will result in five concrete deliverables:

1. A database of 17 case studies with, over at least some time-intervals, integrated archaeological radiocarbon, paleoecological, and archaeological data on social integration.
2. R and Python code for integrating paleoecological datasets with archaeological radiocarbon datasets that will be published in conjunction with our partners (e.g., HOPE and CLaSS).
3. Publications comparing changes in the variability of paleoclimate records with changes (or lack thereof) in paleo-population and vegetation records across our core case studies, as well as individual case study publications. Working group members will also continue to form teams to develop a series of other funding proposals to support various components of the PEOPLE 3000 project.
4. Population estimates from North America, South America, and China for refining the HYDE model.
5. A basic story map of our project for dissemination in our institutions and associated outreach organizations (museums). These story maps will aid our town hall dialog as we present the story of our group and research.