As biological and linguistic diversity, the world's cultural diversity is on decline. However, to date there are no estimates of the rate at which the specific cultural traits of a group disappear, mainly because we lack empirical data to assess how the cultural traits of a given population change over time. Here we estimate changes in cultural traits associated to the traditional knowledge of wild plant uses among an Amazonian indigenous society. We collected data among 1151 Tsimane' Amerindians at two periods of time. Results show that between 2000 and 2009, Tsimane' adults experienced a net decrease in the report of plant uses ranging from 9% (for the female subsample) to 26% (for the subsample of people living close to towns), equivalent to a 1 to 3 % per year. Results from a Monte Carlo simulation show that the observed changes were not the result of randomness. Changes were more acute for men than for women and for informants living in villages close to market towns than for informants settled in remote villages. The Tsimane' could be abandoning their traditional knowledge as they perceive that this form of knowledge do not equip them well to deal with the new socio-economic and cultural conditions they face nowadays.
New concepts like agent-based modelling are providing social scientists with new tools, more suited to their background than other simulation techniques. The success of this new trend will be strongly related to the existence of simulation tools capable of fulfilling the needs of these disciplines. Given the computational requirement of realistic agent-based models, high-performance computing infrastructure is often necessary to perform the calculations. At present, such resources are unlikely to be available to humanities researchers. Having developed Pandora, an open-source framework designed to create and execute large-scale social simulations in high-performance computing environments, this work presents an evaluation of the impact of cloud computing within this context. We find that the constraints of the cloud environment do not have a significant impact on the generic pattern of execution, providing a cost-effective solution for social scientists.
Based on archaeological evidence from Kutch-Saurashtra (N Gujarat, NW India), we use Agent-Based Modelling (ABM) to explore the persistence of hunter-gatherer (HG) groups in semi-arid environments in the mid and late Holocene. Agents interact within a realistic semi-arid environment dominated by the monsoon. Precipitation trends are modelled from instrumental records (1871 -2008) calibrated with existing models for the Asian monsoon in the Holocene (c. 12 ka -present). Experiments aim at exploring dependencies between population dynamics and climate-driven environmental change (in terms of resource availability) for precipitation patterns at the local, regional and continental scales. Resources are distributed across a simplified ground-model. Average yearly precipitation (AYP, i.e. mean) and variance in yearly precipitation (VYP, i.e. standard deviation) are the main parameters affecting resource availability in the simulations. We assess the effects of environmental change on HG populations at different time-scales: (1) Patterns of seasonal (inter-annual) resource availability, (2) Effects of changes in mean precipitation trends over the long (Pleistocene-Holocene) and the mid (Holocene, millennial) periods, and (3) Effects of intra-annual precipitation variability, i.e. changes in standard deviation from mean precipitation trends over the short period (annual to decadal). Simulations show that: (1) Strong seasonality is coherent with the persistence of HG populations in India, independently of the geographical scale of the precipitation models, (2) Changes in AYP over the mid period (Holocene) are not sufficient to explain the disappearance of HG populations in KutchSaurashtra (K-S) 4 ka, (3) Precipitation variability (VYP) over the short period (annual to decadal) is the main parameter affecting population performance and overall ecosystem dynamics. To date, sufficiently refined palaeo-climatic records do not exist for the study area, but higher VYP values 4 ka do not exclude the possibility that other factors may have driven the disappearance of HG populations in Kutch-Saurashtra.
Complexity science refers to the theoretical research perspectives and the formal modelling tools designed to study complex systems. A complex system consists of separate entities interacting following a set of (often simple) rules that collectively give rise to unexpected patterns featuring vastly different properties than the entities that produced them. In recent years a number of case studies have shown that such approaches have great potential for furthering our understanding of the past phenomena explored in Roman Studies. We argue complexity science and formal modelling have great potential for Roman Studies by offering four key advantages: (1) the ability to deal with emergent properties in complex Roman systems; (2) the means to formally specify theories about past Roman phenomena; (3) the power to test aspects of these theories as hypotheses using formal modelling approaches; and (4) the capacity to do all of this in a transparent, reproducible, and cumulative scientific framework. We present a ten-point manifesto that articulates arguments for the more common use in Roman Studies of perspectives, concepts and tools from the broader field of complexity science, which are complementary to empirical inductive approaches. There will be a need for constant constructive collaboration between Romanists with diverse fields of expertise in order to usefully embed complexity science and formal modelling in Roman Studies.
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