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Simpson, Ian A.; Adderley, W. Paul; Guðmundsson, Garðar; Hallsdóttir, Margrét; Sigurgeirsson, Magnús Á.; Snæsdóttir, Mjöll

doi:10.1023/a:1021161006022

Cited by 45 publications

(3 citation statements)

References 23 publications

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“…It is thought that barley became a prestige crop in Iceland which was mainly grown at high status farms because of the large input of resources required to cultivate it successfully (Zori et al 2013;Riddell et al 2018). If so, it is perhaps not surprising that decline and abandonment occurred when grain imports were common as a result of the stockfish trade (Mehler 2011) and when outbreaks of plague in the fifteenth century (Streeter et al 2012) probably reduced the supply of labor needed for cultivation and applying manures (Simpson et al 2002). Increasing erosion on lowland farms (Streeter et al 2012) may have further reduced productivity.…”

Section: Discussionmentioning

confidence: 99%

Climatic controls on the survival and loss of ancient types of barley on North Atlantic Islands

Martin¹,

Brown

George

et al. 2023

Climatic Change

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For ancient types of barley at sites in the Scottish Isles, Faroes, and Iceland, we calculated minimum temperature requirements for grain production (grain production threshold, GPT) as accumulated degree days over the cropping season. Site suitability for barley from AD 1200 to 2000 was investigated by comparing these thresholds with reconstructions of annual cropping season degree days (CSDD) using temperature and tree-ring data. In Iceland, between AD 1200 and 1500, reconstructed CSDD were more favorable in the southwest (Reykjavik), with fewer years below the GPT, than in the North, East and West, but there were two periods (1340–1389 and 1426–1475) with low average CSDD and several years below the GPT which possibly influenced the abandonment of barley cultivation around this time. Reconstructed CSDD for the Faroes (Tórshavn) had only one year below the GPT, but 15 periods of four or more consecutive years with low CSDD which would have challenged barley cultivation, especially in the thirteenth century. Reconstructed CSDD were highest for the Scottish Isles, allowing a more prominent role of barley in the farming system and economy. Nevertheless, years with poor harvests or famines were common and about half were associated with low CSDD, resulting in a significant temperature link but also demonstrating the important contribution of other factors. Despite frequent unfavorable years in both the Faroes and Scottish Isles, resilient production systems, well-adapted barley strains and socio-economic factors allowed barley cultivation to continue, and some ancient types to survive to the present day.

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Section: Discussionmentioning

confidence: 99%

Climatic controls on the survival and loss of ancient types of barley on North Atlantic Islands

Martin¹,

Brown

George

et al. 2023

Climatic Change

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show abstract

“…Such information provided specific soil properties, each stored as single digital raster layer (agricultural suitability, depth of vegetal soil, soil skeleton, water saturation capacity, water storage capacity, soil permeability capacity, nutrient storage capacity) ranked each into five or six classes based on the different aptitude of the soil for the specific characteristic (Table 1). Soil properties are considered to be significant factors in determining agricultural productivity, which, in turn, shapes the Roman site distribution patterns (Simpson et al 2002;Westcott & Brandon 1999). Intensive land use changes and deforestation occurred during the Roman period, probably related to the introduction of agriculture and to the mass movements of human population.…”

Section: Predisposing Factorsmentioning

confidence: 99%

An Explorative Application of Random Forest Algorithm for Archaeological Predictive Modeling. A Swiss Case Study

Castiello¹,

Tonini²

2021

Journal of Computer Applications in Archaeology

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The present work proposes an innovative approach to surveys and demonstrates the effectiveness of bringing together traditional archaeological questions, such as the exploration and the analysis of settlement patterns, with the most innovative technologies related to Machine Learning. Namely, we applied Random Forest, an ensemble learning method based on decision trees, to perform archaeological predictive modeling (APM) for the Canton of Zurich, in Switzerland. This was done based on a dataset of known archaeological sites dating back to the Roman Age. The APM represents an automated decision-making and probabilistic reasoning tool that is relevant for archaeological risk assessment and cultural heritage management. Machine learning-based approaches can learn from data and make predictions, starting from the acquired knowledge, through the modeling of the hidden relationships between a set of observations, representing the dependent variable (i.e. the archeological sites), and the independent variables (i.e. the geo-environmental features prone to influence the site locations). The main objective of the present study is to assess the spatial probability of presence for Roman settlements within the study area. As results, we produced: 1) a probability map, expressing the likelihood of finding a Roman site at different locations; 2) the importance ranking of the geo-environmental features influencing the presence of the archeological sites. These outputs in our results are of paramount importance, not only in verifying the reliability of the data, but also in stimulating experts in different ways. Also, these results help evaluate the benefits and constraints of using such innovative techniques and, ultimately, help explore the performance of machine learning-based models in processing archaeological information.

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“…In Amazonia, the debate about the relationship between soils, population growth and settlement patterns has historically been dominated by Meggers' view that Amazonian poor soils hindered cultural development and allowed only the existence of small nomadic groups (Meggers, 1954(Meggers, , 1971). Meggers' position has been regarded as the "standard model" of Amazonian prehistory (Stahl, 2002). As the establishment of large and permanent settlements is the prerequisite for the development of complex societies (Johnson and Earle, 2000), according to the standard model, the formation of complex societies in Amazonia was impossible for ecological reasons.…”

Section: Introductionmentioning

confidence: 99%

Soil properties and pre-Columbian settlement patterns in the Monumental Mounds Region of the Llanos de Moxos, Bolivian Amazon

Lombardo¹,

Denier²,

Veit³

2014

Preprint

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Abstract. In the present paper we explore to what degree soil properties might have influenced pre-Columbian settlement patterns in the Monumental Mounds Region (MMR) of the Llanos de Moxos (LM), Bolivian Amazon. Monumental mounds are pre-Hispanic earth buildings and were preferentially built on mid to late Holocene paleo levees of the Grande River (here denominated PR1), while levees of older paleorivers (PR0) were only sparsely occupied. We dug two transects across PR0 and PR1 levee-backswamp catenas and analysed them for grain size, pH, CEC and Corg. Our data show that PR1 soils, where the density of mounds is higher, have far greater agricultural potential than PR0 soils, which are affected by aluminium toxicity in the backswamps and by high levels of exchangeable sodium in the levees. This study provides new data on the soil properties of the south-eastern Bolivian Amazon and reinforces the thesis that environmental constraints and opportunities exerted an important role on pre-Columbian occupation patterns and the population density reached in the Bolivian Amazon.

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Cited by 45 publications

References 23 publications

Climatic controls on the survival and loss of ancient types of barley on North Atlantic Islands

Climatic controls on the survival and loss of ancient types of barley on North Atlantic Islands

An Explorative Application of Random Forest Algorithm for Archaeological Predictive Modeling. A Swiss Case Study

Soil properties and pre-Columbian settlement patterns in the Monumental Mounds Region of the Llanos de Moxos, Bolivian Amazon

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