AGRICULTURE AS NICHE CONSTRUCTION: ECO-CULTURAL NICHE EVOLUTION DURING THE NEOLITHIC (c. 6200 - 4900 BC) OF THE STRUMA RIVER VALLEY
A Thesis Submitted to the Committee on Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Master of Arts in the Faculty of Arts and Science
TRENT UNIVERSITY Peterborough, Ontario, Canada (c) Copyright by Brent Robbie Whitford 2017 Anthropology M.A. Graduate Program September 2017
Abstract
Agriculture as Niche Construction: Eco-Cultural Niche Evolution During the Neolithic (c. 6200 – 4900 BC) of the Struma River Valley
Brent Robbie Whitford
The Neolithic Period (c. 6200 – 4900 BC) in the Struma River Valley led to numerous episodes of cultural diversification. When compared with the neighbouring regions, the ecological characteristics of the Struma River Valley are particularly heterogeneous and the Neolithic populations must have adapted to this distinctive and localized ecological setting. It then becomes reasonable to ask if the evolution of cultural variability in the
Struma River Valley was at least partially driven by the ecological setting and differentiation in the evolution of the early agricultural niche. In this thesis, I apply an approach based on niche construction theory and Maxent species distribution modeling in order to characterize the relationship between culture and ecology during each stage of the
Neolithic Period and to assess diachronic change. An interpretation of the results demonstrates that the continuous reconstruction of the early agricultural niche allowed for settlement expansion into new eco-cultural niches presenting different natural selection pressures and that cultural change followed. I also found that cultural and historical contingencies played an equally important role on the evolution of populations and that ecological factors alone cannot account for the numerous episodes of cultural diversification that occurred throughout the region.
Keywords: Neolithic, agriculture, niche construction, ecological niche, eco-cultural niche modeling, Bulgaria, Greece.
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Acknowledgments
First and foremost, I would like to thank Dr. Małgorzata Grębska-Kulova for having introduced me to the Struma River Valley and its many fascinating archaeological complexities. I truly do appreciate your constant help and support and this work could not possibly have been accomplished without you. I would also like to extend my sincerest gratitude to Dr. James Conolly for agreeing to supervise this research and in providing extremely helpful guidance and feedback all throughout the process. To my committee members Dr. Laure Dubreuil and Dr. Rodney Fitzsimons, and to my external examiner Dr.
André Costopoulos for their very useful revisions. To Joanne and Dwaine Whitford (mom and dad) for your everlasting moral and emotional support. And a special thank you also goes to my best friend and esteemed colleague Annapaola Passerini. Your example and our many fruitful discussions have in no small measure helped me to persevere.
Also, thank you to Drs. Bakamska, Genadieva, and Malamidou for your help in obtaining the necessary data and to Drs. Y. Boyadzhiev, K. Boyadzhiev, and I. Vajsov for your occasional commentary. This research was funded in part by the Social Sciences and
Humanities Research Council of Canada (SSHRC) and the Michael Smith Foreign Study supplement as well as by the Ontario Graduate Scholarship and the Sandi Carr Award.
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Table of Contents
Abstract ...... ii
Acknowledgments ...... iii
Table of Contents ...... iv
List of Figures ...... ix
List of Tables ...... x
Chapter 1 – Introduction ...... 1
1.1 Research problem ...... 1
1.2 Theoretical overview ...... 2
1.3 Archaeological context ...... 4
1.4 Methodological framework ...... 5
1.5 Expected outcomes ...... 6
Chapter 2 – Theory ...... 9
2.1 Niche construction and the eco-cultural niche ...... 9
2.2 Niche construction and eco-cultural niche applications to archaeology ...... 11
2.2.1 Applications of Niche Construction Theory ...... 13
Smith on the application of NCT to the domestication of plants and animals ...... 13
Rowley-Conwy and Layton on foraging and farming as niche construction ...... 15
2.2.2 Eco-cultural niche applications ...... 19
Galletti et al. on the eco-cultural distribution of ancient and modern agricultural terraces ...... 19
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Banks et al. on considerations to the eco-cultural niches of Europe’s first farmers ...... 21
2.3 Niche construction and the eco-cultural niche as an inheritance system ...... 23
Chapter 3 – Framing the Question...... 26
3.1 Archaeological Context ...... 26
3.2 Landscape and climate ...... 28
3.2.1 Geography of the Struma River Valley ...... 28
3.2.2 Climate characteristics ...... 31
3.3 The Neolithic chrono-cultural periodization system ...... 33
3.3.1 The Early Neolithic (6200 - 5450 cal BC) ...... 35
3.3.2 The Middle Neolithic (5450 - 5200 cal BC)...... 38
3.3.3 The Late Neolithic (5200 – 4900 cal BC) ...... 41
3.4 Subsistence Practices ...... 44
3.4.1 The faunal record ...... 44
Early Neolithic ...... 44
Middle Neolithic ...... 45
Late Neolithic ...... 47
3.4.2 Paleobotanical investigations ...... 48
Early Neolithic ...... 48
Middle Neolithic ...... 50
Late Neolithic ...... 51
3.5 Was the spread of Neolithic settlement across the Struma River Valley an adaptive
expansion? ...... 52
Chapter 4 – Data and Methods ...... 54
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4.1 Considerations in eco-cultural niche modeling ...... 54
4.1.1 Developing the modeling framework ...... 54
4.1.2 Setting the diachronic schema...... 55
4.2 Data: archaeological settlements ...... 56
4.2.1 Defining the archaeological population ...... 56
4.2.2 Neolithic settlements in the Struma River Valley ...... 57
4.3 Data: ecological variables ...... 61
4.3.1 Assessing the relevance and availability of ecological variables ...... 61
4.3.2 Characterizing the ecological setting of the Struma River Valley ...... 62
4.4 Methodological approach ...... 65
4.4.1 Pearson’s test for statistical collinearity ...... 65
4.4.2 Selecting the modeling algorithm: Maxent ...... 66
4.4.3 Evaluating Maxent model performance: ENMeval ...... 69
4.5 Interpreting the results ...... 72
4.5.1 Statistics for interpretation: Maxent and ENMTools ...... 72
4.6 Summary – Data and Methods ...... 75
Chapter 5 – Application and Results ...... 77
5.1 Implementing the methodological approach ...... 77
5.2 Assessing statistical collinearity between independent variables—Pearson’s test ...... 77
5.3 Producing the eco-cultural niche models—ENMeval and Maxent ...... 81
5.3.1 Selecting the modeling parameters—ENMeval ...... 81
Early Neolithic: ENMevaluation...... 83
Middle Neolithic: ENMevaluation ...... 84
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Late Neolithic: ENMevaluation ...... 85
Vinča B—Late Neolithic subset: ENMevaluation ...... 85
Topolnitsa/Akropotamos—Late Neolithic subset: ENMevaluation ...... 86
5.3.2 Running the modeling algorithm—Maxent ...... 88
5.4 Generating metrics for interpretation—Maxent and ENMTools ...... 88
5.4.1 Maxent model results and metrics for interpretation ...... 90
The Early Neolithic eco-cultural niche model ...... 90
The Middle Neolithic eco-cultural niche model ...... 93
The Late Neolithic eco-cultural niche model ...... 95
Vinča B-Late Neolithic subset eco-cultural niche model ...... 98
Topolnitsa/Akropotamos-Late Neolithic subset eco-cultural niche model ...... 100
5.4.2 Eco-cultural niche overlap and breadth statistics—ENMTools ...... 102
5.5 Application and results—summary ...... 104
Chapter 6 – Interpretation ...... 106
6.1 Defining the eco-cultural niche ...... 106
6.1.1 Issues of interpretation...... 107
6.2 The Early Neolithic eco-cultural niche ...... 108
6.3 The Middle Neolithic eco-cultural niche ...... 110
6.3.1 Niche construction in the Middle Neolithic and divergence of the eco-cultural niche ...... 113
6.4 The Late Neolithic eco-cultural niche ...... 114
6.4.1 The Vinča B Late Neolithic subset eco-cultural niche ...... 116
6.4.2 The Topolnitsa/Akropotamos Late Neolithic subset eco-cultural niche ...... 119
6.5 Diachronic considerations in eco-cultural niche evolution ...... 121
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6.6 The relationship between culture and ecology during the Neolithic Period ...... 123
Chapter 7 – Conclusion ...... 126
7.1 Agriculture as niche construction ...... 126
7.2 Directions for future research ...... 127
7.2.1 In consideration of different ecological variables ...... 128
7.2.2 In consideration of additional cultural variables ...... 129
7.2.3 In consideration of niche construction ...... 129
7.2.4 In consideration of directionality, cultural contacts, and potential for movement ...... 131
7.3 Conclusion ...... 131
References Cited ...... 134
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List of Figures
Figure 1: Eco-cultural niche correlative descent with modification model...... 24
Figure 2: The Struma River Valley...... 30
Figure 3: Early Neolithic settlements...... 37
Figure 4: Middle Neolithic settlements...... 40
Figure 5: Late Neolithic settlements...... 43
Figure 6: Independent environmental variables...... 64
Figure 7: Pearson’s test for statistical collinearity (red borders = R2 > 0.8)...... 78
Figure 8: Early Neolithic ENMevaluation results (optimum parameters indicated with star)...... 83
Figure 9: Middle Neolithic ENMevaluation results (optimum parameters indicated with star)...... 84
Figure 10: Late Neolithic ENMevaluation results (optimum parameters indicated with star)...... 85
Figure 11: Vinča B ENMevaluation results (optimum parameters indicated with star)...... 86
Figure 12: Topolnitsa/Akropotamos ENMevaluation results (optimum parameters indicated with star). ... 87
Figure 13: Maxent eco-cultural niche models...... 89
Figure 14: Early Neolithic independent variable response curves...... 92
Figure 15: Middle Neolithic independent variable response curves...... 94
Figure 16: Late Neolithic independent variable response curves...... 97
Figure 17: Vinča B independent variable response curves...... 99
Figure 18: Topolnitsa/Akropotamos independent variable response curves...... 101
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List of Tables
Table 1: Chrono-cultural periodization system; after Perničeva 2007...... 35
Table 2: Absolute date ranges for the Bulgarian Neolithic; after Boyadziev 1995...... 35
Table 3: Archaeological settlements by chrono-cultural attribution...... 60
Table 4: Independent environmental variables...... 63
Table 5: Maxent Feature class types; after Phillips et al. 2006; 2008...... 70
Table 6: Independent ecological variables retained after Pearson's test...... 79
Table 7: Soil types and surface area (ESDAC)...... 80
Table 8: Early Neolithic independent variable percent contribution and permutation importance...... 92
Table 9: Middle Neolithic independent variable percent contribution and permutation importance...... 94
Table 10: Late Neolithic independent variable percent contribution and permutation importance...... 97
Table 11: Vinča B independent variable percent contribution and permutation importance...... 99
Table 12: Topolnitsa/Akropotamos independent variable percent contribution and permutation importance.
...... 101
Table 13: Schoener’s D niche overlap statistic (0 = no overlap, 1 = perfect overlap)...... 103
Table 14: the I method niche overlap statistic (0 = no overlap, 1 = perfect overlap)...... 103
Table 15: Relative rank niche overlap statistic (0 = no overlap, 1 = perfect overlap)...... 103
Table 16: Niche breadth statistic; after Levins 1968...... 104
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Chapter 1 – Introduction Investigating the relationship between culture and ecology during the Neolithic Period of the Struma River Valley
1.1 Research problem
The Neolithic Period—defined in this thesis as the period following the adoption of early agricultural practices up to the introduction of copper metallurgy—represents a particularly evident shift with regards to the relationship between culture and ecology. The domestication of plants and animals in Southwest Asia, it has been argued, was an adaptive innovation in human subsistence practices that led to a relatively rapid Neolithic expansion from its area of origins into Central Asia and Southeastern Europe, either by diffusion or alongside the migration of human populations (Rowley-Conwy and Layton 2011). Upon the transference of agricultural practices to novel ecological conditions, it can be inferred that natural selection pressures modified subsistence practices to better suit the new conditions in which agriculture was introduced. However, the relationship between culture and ecology is reciprocal suggesting, that the introduction of agriculture can also modify natural selection pressures as well and stimulate cultural evolution in that regard. Therefore, by characterising change to the reciprocal relationship between culture and ecology during the Neolithic Period we stand to better understand the mechanisms and processes of evolution operating on early agricultural societies.
In the Struma River Valley—located in Southwest Bulgaria and Northern Greece— agricultural practices were first introduced around 6200 cal BC and from there crossed the
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threshold between the Mediterranean and Continental climatic and vegetational zones.
When compared with the neighbouring regions to the immediate north and south, the ecological characteristics of the Struma River Valley are particularly heterogeneous and the Neolithic populations must have adapted to this distinctive and localized ecological setting. Furthermore, throughout the Neolithic Period, for approximately 1,300 years—the region is marked by significant episodes of cultural diversification and shifts in settlement patterns (Grębska-Kulova 2004). The latter therefore begs the question as to whether or not the heterogeneous ecological characteristics of the Struma River Valley played a role in the cultural evolutionary process during the Neolithic Period and if so to what degree. Can particular cultural traits be associated with distinct ecological conditions within the valley?
And can the observed instances of cultural diversification be correlated with shifts to the eco-cultural niche? By developing and diachronically assessing eco-cultural niche models for the Neolithic Period, the implications of the relationship between culture and ecology in the Struma River Valley will be investigated.
1.2 Theoretical overview
Understanding the relationship that exists between humans and their environments has long played an important role in addressing archaeological problems, and more specifically with regards to elaborating on the processes of cultural evolution. Beginning with cultural ecology (Butzer 1971; Steward 1955) through human behavioural ecology (Winterhalder and Smith 2000), and dual inheritance theory (Boyd and Richerson 1985) to the more recent development of niche construction and triple inheritance theory (Odling-Smee et al. 2003),
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explaining how culture interacts with the environment has become a near constant in the disciplines of anthropology and archaeology.
In this thesis, I will primarily apply the methodology of the eco-cultural niche (Banks et al. 2006) to identify the changing relationship between human settlement and its ecological setting. To explain the eco-cultural relationships and how they change, I have chosen to use niche construction theory. Although partially rooted in the earlier cultural ecology of Julian
Steward, it deviates from adaptionist standard evolutionary theory (SET), because the latter often neglects to explicitly acknowledge the reciprocal relationship that exists between culture and the environment in favor of a top down approach in which the environment drives the process of natural selection and adaptation (Odling-Smee et al. 2003; Smith
2009). Far from discounting the influence of the environment, however, an approach based on niche construction theory instead aims to integrate alternative considerations that include the ability of humans to influence their own evolutionary process via the modification of natural selection pressures. Chapter 2 then serves to outline the concepts of niche construction and of the eco-cultural niche and considers their potential for synthesis.
A directed literature review of relevant seminal works (Banks et al. 2013; Galletti et al.
2013; Rowley-Conwy and Layton 2011; Smith 2007b) is also correspondingly presented and evaluated. In conclusion, I argue that agricultural practices may be taken as a form of niche construction and that niche construction is an indispensable component of the eco- cultural niche. I discuss how the eco-cultural niche is essentially inheritable—having been at least in part defined by niche construction—and that it is therefore evolutionarily consequential. Guided by the principle of correlative descent with modification, an integrated eco-cultural niche inheritance model is then put forward.
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1.3 Archaeological context
Agriculture was first introduced to the Struma River Valley around 6200 cal BC after having been transferred from the Near-East to the East Mediterranean and then northward into Continental regions (Grębska-Kulova 2004; Marinova et al. 2012; Nikolov 2007).
Extending 415 kilometers from north to south, the Struma River Valley effectively straddles the transitional space between the Mediterranean and Continental climatic and vegetational zones and as such is characterized by substantial latitudinal ecological heterogeneity. Furthermore, the Struma River Valley is primarily a mountainous region subdivided by a complex system of intermittent gorges and drainage basins providing a myriad of possible ecological niches along the vertical gradient of the valley slopes as well.
Early agricultural populations in the region then may have been subjected to a number of different possible ecological selection pressures. A diachronic investigation on the relationship between culture and the environment during the Neolithic Period of the Struma
River Valley is thus warranted in consideration of the cultural evolutionary process.
Chapter 3 consists of a problem-oriented review on the history of research concerning the Neolithic Period in the Struma River Valley. First, the geography and climate of the region is described in order to characterize the study region and its heightened degree of ecological variability. Second, an overview of the Neolithic chrono-cultural periodization system—from the Early Neolithic to Late Neolithic—is presented in order to define the archaeological populations in question. And third, a general discussion on subsistence and land-use practices is inferred from investigations regarding the paleobotanical and faunal records of Neolithic settlements. By reviewing the temporal and regional characteristics of
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the Neolithic Period in the Struma River Valley, I make the general observation that the heterogeneous ecological characteristics of the region do in fact appear to have impacted the cultural evolutionary process—there is a noticeable trend towards heightened cultural variability between different sub-regions over time. It therefore becomes reasonable to ask whether the evolution of cultural variability is at least in part driven by the heterogeneous ecological setting of the Struma River Valley and directed by differentiation to the eco- cultural niche.
1.4 Methodological framework
Recently, ecological niche modeling techniques have been adapted towards elaborating on the relationship between culture and ecology based on the quantitative evaluation of human settlement distributions across geographic and environmental space (for relevant examples see Banks et al. 2008; Conolly et al. 2011; Galletti et al. 2013). As such, ecological niche models may be utilized to more effectively characterize and interpret the mechanisms and processes of cultural evolution. To that end, I designed a diachronic eco-cultural niche modeling framework (Banks et al. 2006; Muscarella et al. 2014; Peterson 2011; Warren et al. 2008) in consideration of the primary research question using the R package for statistics
(R Core Team 2015) and Maxent species distribution models (Phillips et al. 2006; Phillips and Dudik 2008).
Although the technical considerations of eco-cultural niche modeling are numerous, they can be tailored to a specific research question and relevant modeling parameters identified.
Chapter 4 therefore serves to elaborate on the data selection process as well as on the
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methodological framework and its incremental steps. The criteria used in identifying distinct archaeological populations and in the selection of relevant ecological variables for the purposes of constructing eco-cultural niche models are presented and discussed.
Concerning the methodological approach, the application of species distribution models
(SDMs) to archaeological problems is introduced, and the Maxent modeling approach is thoroughly described. Considerations regarding the evaluation of Maxent model performance are then scrutinized, and lastly tools used in the interpretation of eco-cultural niche models are suggested. The latter diachronic eco-cultural niche modeling framework is primarily designed with the intent to produce models that can be used to assess change to the eco-cultural niche and identify its potential relationship with regards to the cultural evolutionary process.
1.5 Expected outcomes
The final eco-cultural niche models will be utilized to both qualitatively and quantitatively assess the relationship between culture and ecology in the Struma River Valley during the
Neolithic Period. Furthermore, the diachronic investigation will allow for the identification of change to the eco-cultural niche over time bearing reference to the cultural evolutionary process. The application of niche construction theory will first and foremost serve to highlight the reciprocal nature of the relationship between culture and the environment by placing a focus on the ability of humans to actively modify their ecological constraints— rather than simply adapt to environmental selection pressures. Therefore, it should be emphasized that early agricultural societies may have in part directed their own
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evolutionary process via niche construction. In other words, it is anticipated that natural selection pressures will only partially account for the development and distribution of particular cultural traits and that specific historical and cultural contingencies will be found to have also played a role in determining the distribution of cultural traits across geographic and ecological space. Nonetheless, it is also expected that certain subsistence and land-use practices will be constrained by particular ecological conditions and will correlate more strongly with specific eco-cultural niches. The process of cultural diversification may then have also been impacted in this regard. Chapter 5 will present the results of the eco-cultural niche modeling framework and Chapter 6 will consist of the interpretations.
As previously mentioned, the Neolithic Period marks a particularly evident shift with regards to the relationship between culture and ecology. It is therefore likely that similar cases as those that occurred in the Struma River Valley may also be found to have occurred elsewhere and in different archaeological contexts. Considering that agriculture has often been transferred to novel ecological conditions, in almost every case natural selection pressures would have been modified, having the potential to impact the cultural evolutionary process. The development and spread of agricultural practices in general then may be characterized as a large-scale and reoccurring niche construction event presenting obvious evolutionary consequences that extend far beyond the Struma River Valley alone.
To better understand the evolutionary consequences of the transference and development of agriculture as a niche construction event is therefore the ultimate aim of this study.
Chapter 7 will outline the conclusion of the investigations and identify some directions for future research. It is hoped that the following investigations on the relationship between culture and ecology during the Neolithic Period of the Struma River Valley will then also
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contribute towards elaborating on the process of cultural evolution within early agricultural societies more generally.
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Chapter 2 – Theory The eco-cultural niche as an inheritance system
2.1 Niche construction and the eco-cultural niche
This thesis is informed by the concepts of ecological niche and of niche construction.
Ecological niche may be defined as the total set of environmental conditions within which a species can subsist and thrive (Grinnell 1917) and its volume calculated from the multi- dimensional space within which all of those environmental conditions are met (Hutchinson
1957). Niche construction, on the other hand, may be defined as the effects that an organism presents to its ecological niche in modifying natural selection pressures (Odling-Smee et al. 2003). In simpler words, niche construction theory (NCT) states that organisms do not simply live within their ecological niche, but that they also actively modify it through their day-to-day activities (Odling-Smee et al. 2003). The end result, according to niche construction theorists, is that the organism may actually come to modify its own selective environment—and also that of other organisms—via niche construction (Odling-Smee et al. 2003). Therefore, organisms can inadvertently direct their own evolutionary process both in cultural and biological terms by modifying their ecological niche (Odling-Smee et al. 2003). Humans, in their possession of uniquely elaborate cultural repertoires, it has also been argued, may in fact be the most potent niche constructors of all (Laland and O’Brien
2010; Odling-Smee et al. 2003; Odling-Smee and Laland 2012; Smith 2007a).
In short, the fundamental premise of niche construction is that organisms, including humans, are active rather than passive actors in the evolutionary process; the relationship
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between organisms and the environment is reciprocal. It has therefore been proposed that niche construction must be considered an integral process of evolution (Odling-Smee
2003), though not without its criticisms (see Dawkins 2004; Scott-Phillips et al. 2014). For example, skeptics of niche construction theory claim that NCT “conflates evolutionary processes with the causes of those processes” (Scott-Phillips et al. 2014:1235), suggesting that while niche construction may in fact help in determining how particular natural selection pressures are created and/or mitigated, it is not in itself a process of evolution.
However, it is equally important to note that both the skeptics and advocates of NCT agree that niche construction does at least play a causal role in how evolutionary processes occur.
Thus, with regards to evolution and the conclusion that niche construction must be considered an integral process, organisms are already viewed as active actors within the cultural evolutionary process. It is therefore suggested that so far as culture as an inheritance system is concerned, niche construction (as a meaningfully descriptive term) may be well integrated into the already existing framework as defined by Boyd and
Richerson (1985) without necessary need for recourse to extraneous processes. Niche construction and its effects are then perhaps best viewed as nothing other than a component of culture whenever the niche construction activity considered is in fact the result of cultural rather than biological activity.
In this regard, in order to distinguish the human cultural from the purely biological niche,
Banks et al. (2006) have termed the ecological niche of human cultures the eco-cultural niche. Banks and colleagues (2006) suggest that by analyzing the distribution of culturally adaptive systems, the eco-cultural niche of specific human populations may be identified in geographic and ecological space. The latter then also implicitly accounts for cultural
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niche construction as it assumes from the outset that cultural adaptations in part both define and create the human ecological niche. The eco-cultural niche, having been in part defined by the properties and ecological distribution of a culturally adaptive system, is therefore always related to culture and niche construction. Likewise, the eco-cultural niche is necessarily situated in environmental space (i.e. in reference to the geographic distribution of ecological variables), suggesting that environmental selection pressures are also an indispensable component of the system (Banks et al. 2006). As such, the working of the eco-cultural niche is defined by the reciprocal relationship between culture and environment. It then follows that when changes are identified in an eco-cultural niche, this provides insight into cultural evolution, while bearing references to the effects of niche construction.
2.2 Niche construction and eco-cultural niche applications to archaeology
The addition of niche construction theory (NCT) and of eco-cultural niche applications to archaeology in analyzing particular evolutionary pathways is not a new consideration. In fact, many applications of NCT and/or of the eco-cultural niche have as of late multiplied in the relevant literature. However, their potential relationship with one another has yet to be explicitly recognized. While considerations of the relationship between culture and the ecological niche have most certainly appeared before, under the purview of cultural ecology
(Steward 1955), dual inheritance theory (Boyd and Richerson 1985), and/or human behavioural ecology (see Winterhalder and Smith 2000 for an overview), most up to this point have been strictly based on a top down approach bracketed by standard evolutionary
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theory (SET) in which the environment is driving the process of natural selection and adaptation (Smith 2009). The reverse possibility, that the environment could also be adapted to culture and/or biology via niche construction, was rarely if ever considered.
Also, while the notion that culture can fundamentally impact the process of evolution was introduced quite early on (see Brace 1967), culture was taken rather as having replaced natural selection as opposed to inciting change or mitigating its effects. For example, Brace
(1967) essentially argued that “culture as an ecological niche” supersedes ecology in consideration of the evolutionary process, which then lies at the opposite extreme of the spectrum with regards to the relationship between culture and ecology.
The explicit addition of NCT to archaeology from the mid-2000s thus allowed for more nuanced interpretations that directly acknowledged the reciprocal relationship between organism, culture, and environment, often leading towards radically different conclusions as compared with an approach based solely on SET or on culture as the ecological niche
(Kendal et al. 2011; Kluiving 2015; Rendell et al. 2011; Riede 2011; Rowley-Conwy and
Layton 2011; Shennan 2011; Smith 2007b). The concept of eco-cultural niche, in its explicit characterization of the reciprocal relationship between culture and the environment, could also then be considered a valuable analytical tool to be adapted towards elaborating on the effects of niche construction. As such, niche construction and eco-cultural niche applications in archaeology may be useful to consider in unison. The following literature review then is to provide an overview of niche construction and of eco-cultural niche contributions, as they have most readily been applied, and to assess their mutual similarities and potential for synthesis.
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2.2.1 Applications of Niche Construction Theory
Smith on the application of NCT to the domestication of plants and animals
Smith (2007b) offers one of the first applications of NCT with regards to an archaeological problem. Namely, Smith investigates the applicability of NCT in developing an explanatory framework regarding the domestication of plants and animals. He brings forward a compelling argument that positions niche construction at the interface between the general macro-evolutionary processes on the emergence of domestication and the local/species specific considerations. In other words, Smith attempts to bridge the gap between the question of why domestication first occurred with that of the what, where, and when the domestication of particular species first occurred, by utilizing a niche construction approach.
The specific argument positioned by Smith essentially rests on a series of four observations that may be advanced with regards to the human condition more generally.
First, considering that niche construction has been documented and is nearly ubiquitous within a vast array of species (see Odling-Smee et al. 2003), it is therefore also reasonable to conclude that niche construction has likely played an important role in the evolution of human societies as well. Second, due to our unmatched propensity for culture and cultural transmission, we may also conclude that past human niche construction activities were both sophisticated and under constant refinement. Third, ethnohistoric studies have provided evidence that general human niche construction has been an important component for the development of societies the world over. And fourth, an increasing body of evidence is emerging in support of more fine-grained human niche construction activities resulting in
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ecological change. Likewise, archaeologists and paleo-biologists are becoming more and more sensitive to the evidence that niche construction activities have also occurred and may be recognized in the deep past. Therefore, considering the enlarging body of compelling evidence with regards to niche construction, Smith believes that it is reasonable to assume that niche construction not only occurs, but that it has also occurred in the past and that it was and still is evolutionarily consequential.
With regards to the evolution of plant and animal domestication more specifically, considering that domestication occurred on numerous occasions covering various chronological, geographic, and environmental settings, although analytically suggestive of various local adaptations as the result of changing environmental pressures, the act of domestication itself—as niche construction—points towards a pre-existing and well- established underlying human behavioural framework. In other words, niche construction as a human behavioural framework provided the inherent propensity for the act of domestication as both a naturally and culturally adaptive response. The varying specific considerations and knowledge requirements in terms of the management and domestication of particular species demonstrate that niche construction activities are also contingent on the local environmental setting and specific historical processes. That different species were domesticated at different times and locations, that the same species at times were targeted for domestication by different populations, and that some efforts towards domestication were initially abandoned only to in some cases re-emerge millennia later, further attests to the local contingency of domestication as a niche construction event and also to the persistence of human environmental modification as a general and re-occurring behavioural framework. Therefore, rather than as a series of one-off adaptive responses
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based solely on a shift in environmental selection pressures, Smith believes that the act of domestication can be better attributed to the recurring role of niche construction within human societies as having taken place over many generations with its specific local directions informed by both environmental and cultural processes.
To summarize, according to Smith (2007b), it is not only reasonable but necessary to conclude that niche construction—as a ubiquitous underlying human behavioural framework—has played a role in the evolution of human societies more generally and also specifically in the emergence of plant and animal domestication. To assume otherwise is to ignore the ever-increasing body of evidence that attests to the reciprocal nature of the relationship between humans, culture, and the environment. The domestication of plants and animals is but one particularly potent example of such a niche construction event having taken place in the past. The local contingencies of niche construction, however, depend on the particular relationship between culture and environment at specific times and in specific places. As such, it is here suggested that the identification of the eco-cultural niche at those specific times and places could also provide a framework under which the local contingencies of niche construction may be better understood.
Rowley-Conwy and Layton on foraging and farming as niche construction
Rowley-Conwy and Layton (2011) have approached hunting and gathering as well as agriculture from the lens of niche construction to compare and contrast what they describe as stable vs. unstable adaptations. From their point of view, foraging and farming as acts of niche construction modify the natural environment and impact natural selection
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pressures. While some constructed niches are inherently more stable than others and may persist near indefinitely with little to no need for change, as Rowley-Conwy and Layton argue, others are deemed fundamentally unstable resulting in niche reconstruction and by association then also initiate cultural change. In other words, they suggest that the inherent instability associated with some types of constructed eco-cultural niche—the agricultural niche most especially—ultimately and necessarily leads to additional episodes of niche construction.
First, Rowley-Conwy and Layton recognize that hunter-gatherers engage in several types of activities that may be termed stable niche construction. These include the human induced propagation of concentrated wild plant stands, small-scale cultivation, the burning of vegetation, and the selective hunting of particular animal species at particular age ratios to promote the availability of important wild resources. Collectively, these hunter-gatherer niche construction practices may be termed “low-level food production” in that the populations who utilize them are often very aware of the consequences resulting from their actions. Considering that low-level food production also mitigates natural selection pressures, it then qualifies as niche construction. Second, such types of low-level food production in general may be considered stable forms of niche construction. Rowley-
Conwy and Layton support the former claim on the stability of low-level food production through the invocation of ethnographic data. They demonstrate that most hunting and gathering societies still depend entirely on hunting and gathering or alternatively on low- level food production for the majority of their subsistence needs with little to no need for change or without ever transitioning to agriculture. Additionally, those hunter-gatherer societies that do include agriculture in their practices depend on it for 5% or less of their
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total nutritional intake. Differentially, agricultural societies depend on agriculture for 50% or more of their nutritional needs, while comparatively few societies depend on it for between 5 to 50%. Rowley-Conwy and Layton thus further conclude that the 5 to 50% agricultural dependence zone must be fundamentally unstable and that early agricultural societies would then have had to quickly cross this threshold, ultimately needing to reconstruct their eco-cultural niche and abandon hunting, gathering, and low-level food production as the primary forms of subsistence.
Rowley-Conwy and Layton stress that agriculture is not always the linear result of the intensification of the hunter-gatherer niche. Rather, agriculture is the result of an entirely new type of niche construction as domestication and agriculture can only emerge from a select few types of low-level food production. For instance, in the case of the Near-East, where agriculture was first developed, those species that were domesticated played a relatively minor role in the previous hunter-gatherer niche. In this regard, it has been well supported that climate change resulting from the Younger-Dryas fundamentally altered the ecological landscape of the Near-East and reduced the availability of many wild resources.
The species that were later domesticated, on the other hand, thrived in the new climate.
Furthermore, and most importantly, the hunter-gatherer societies of the region collected the wild ancestors of future domesticates with the use of a sickle, resulting in the unconscious selection of unshattering seed heads. As the unshattering seeds were subsequently returned to the settlement, these could have either been intentionally replanted or unintentionally sown from refuse piles as acts of low-level food production. The latter particular type of low-level food production then would have initiated the process of domestication not by the act itself, but rather by unintentionally selecting for genetic variants of the unshattering
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seed head. Therefore, Rowley-Conwy and Layton argue that the hunter-gatherer niche first needed to be destabilized—in the case of the Near-East occurring as the result of significant environmental change—before the transition to farming occurred and that niche construction as low-level food production was already a significant part of the human behavioural framework. Following this logic, the transition to agriculture was then not the direct result of adaptation to ecological selection pressures but more the unintended result of a particular niche construction practice.
Following the transition to agriculture, as the agricultural niche intensified those societies would have then needed to quickly cross the unstable 5-50% dependence threshold. The comparative wealth of the agricultural niche—having the ability to support more persons per land area and increase birth rates (Lee 1980)— often also results in population increase, which then further drives dependence towards the agriculture niche.
In contrast with stable hunter-gatherer niches and low-level food production practices, which require an intimate and longstanding knowledge of the local environment and a balance in population, the agricultural niche can be exported and adapted to new environments in order to accommodate demographic expansion. As agricultural populations then reached new geographic areas and ecological conditions, the agricultural niche therefore had to be continuously reconstructed in adaptation to new ecological selection pressures as the result of its own inherent instability. Thus, in conclusion, Rowley-
Conwy and Layton argue that the agricultural niche is fundamentally unstable when compared with its hunter-gather counterpart, resulting in the constant reoccurrence of niche construction in order to balance out the resulting population pressures. As such, it may also be suggested that by identifying diachronic change to the agricultural niche, such
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occurrences of niche reconstruction would also be identified. The latter can then provide valuable insights into the process of cultural change as resulting from eco-cultural niche construction.
2.2.2 Eco-cultural niche applications
Galletti et al. on the eco-cultural distribution of ancient and modern agricultural terraces
Galletti and colleagues utilized an ecological niche modeling approach, based on maximum entropy species distribution modeling (Maxent), to determine the potential eco-cultural distribution of ancient vs. modern agricultural terraces in the Troodos foothills of Cyprus
(2013). The construction and use of agricultural terraces represents a particularly evident occurrence of agricultural niche construction resulting from human modification to the environment, presenting long lasting ecological and cultural impacts. The hypothesis advanced by Galletti and colleagues is that differences between the locations of modern and ancient agricultural terraces should have an ecological basis. It could therefore be said that such differences also may constitute a diachronic eco-cultural difference in consideration of niche construction.
Most interesting for the current purposes are Galletti et al.’s findings with regards to differences between the ancient and modern eco-cultural niche models. Through the use of eco-cultural niche models, Galletti and colleagues were able to identify significant differences between the eco-cultural factors that drove selection for particular landscapes regarding agricultural terrace construction in both the ancient and modern case-studies. In the ancient case-study, it was found that the most significant ecological factors for terracing
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were related to surface geology and access to streams—supposed as a source location for arable sediments used in the construction of terrace beds. On the other hand, in the modern case-study, terrain slope is the only significant factor identified in the selection of modern terrace locations, suggesting a less technologically restricted ability to construct viable agricultural terraces over time.
However, as the authors also note, the results of the ecological niche model for the ancient agricultural terraces may reveal more than just a landscape selection based on agricultural terrace construction. The eco-cultural models can also be used to infer additional relationships between culture and environment. For instance, they cite evidence
(see Bevan and Conolly 2011) that the ecological conditions under which ancient terraces can be found might also be associated with any other number of cultural factors here not explicitly sought after by the modeling process. For instance, considerations of surface geology is also directly related to copper acquisition (important during the Bronze Age) and access to streams as a water source is likewise necessary for the intensification of metallurgical practices. Thus, the results of the ancient agricultural terrace model not only provides insight into the ecological conditions for agricultural terrace building, but also on the greater co-evolutionary implications of culture and environment despite that aim not having been the explicit intent of the analyses. It may then be concluded that the latter investigation demonstrates a successful useful basis for the potential of evaluating the diachronic evolutionary impacts of niche construction in light of eco-cultural niche models.
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Banks et al. on considerations to the eco-cultural niches of Europe’s first farmers
Banks and colleagues adapted ecological niche modeling methods, based on genetic algorithm (GARP) and maximum entropy species distribution modeling (Maxent), towards identifying the eco-cultural niches of three Neolithic populations (Cardial Ware, Impressed
Ware, and Linearbandkeramik), who are collectively considered to be largely responsible for the spread of agriculture throughout the European continent at-large (Banks et al. 2013).
Their research questions fundamentally concern the relationship between culture and environment, and thus also potentially the effects of niche construction. Did the environment impose constraints on the spread of particular cultural adaptations? Or, could similar cultural adaptations be spread into a range of different environmental conditions?
Ultimately their aims echo Smith’s local/species specific considerations and are meant to elaborate on whether or not different archaeological cultures occupied distinctive ecological niches, and if so, what potential impacts and considerations may be identified by bearing reference to that eco-cultural relationship.
In terms of their results, the eco-cultural niche models firstly demonstrated that the eco- cultural niches of the Cardial and Impressed Ware cultures overlapped significantly, spanning the length of the Mediterranean climate zone. The latter suggests that the Cardial
Ware and Impressed Ware populations’ subsistence and settlement strategies were both suitable within similar ecological conditions despite there being some differences in terms of their overall cultural repertoire. Therefore, the authors suggest that these results must reveal the spread within a distinct ecological niche of a particular cultural adaptation that is common to both the Cardial and Impressed Ware populations. Therefore, rather than
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possessing mutually exclusive eco-cultural niches bearing reference to their total cultural differences, the distinction between the Cardial and Impressed Ware populations can only be related to historical and/or cultural processes and not to ecological constraints. When comparing the Cardial/Impressed Ware eco-cultural niche to that of the
Linearbandkeramic, however, quite a different scenario emerges. The combined eco- cultural niche of the Cardial/Impressed Ware population is wholly different from that of the Linearbandkeramic, presenting little to no overlap, which in turn informs the existence of a mutually exclusive eco-cultural relationship between the former population and the latter, suggesting that ecological constraints here played a larger role in the distinction between the Linearbandkeramic and the combined Cardial/Impressed ware populations.
In conclusion, the study undertaken by Banks and colleagues demonstrates how the relationship between culture and environment may be characterized and assessed via the use of eco-cultural niche models. The latter is also then potentially useful in assessing the effects of niche construction events that may have occurred within each said cultural populations’ respective eco-cultural niche based on differences to the relationship between culture and the environment. In this regard, what is perhaps most useful about eco-cultural niche models then is the ability to define the reciprocal relationship between population, culture, and environment, ultimately providing a framework under which cultural adaptations (such as niche construction) may be evaluated in light of environmental, historical and, cultural contingencies. Essentially, eco-cultural niche models then define the ecological boundaries within which cultural adaptations (niche construction included) can take place.
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2.3 Niche construction and the eco-cultural niche as an inheritance system
As demonstrated in the literature, the concepts of niche construction and of the eco-cultural niche may be considered to share many similarities and mutual considerations with regards to the evolutionary process. It is here suggested that niche construction cannot really be wholly understood without an elaboration on the eco-cultural niche, and that the eco- cultural niche cannot be adequately identified without also considering niche construction as a ubiquitous human cultural trait. In terms of their explicit relevance to evolution, however, niche construction and the eco-cultural niche are only evolutionary consequential whenever their effects are ultimately inherited (Odling-Smee et al. 2003). Under some circumstances the active modification of the eco-cultural niche via niche construction activities (be they biological or cultural) results in the permanent alteration of the eco- cultural niche and thus also of selection pressures. When the environment and its related selection pressures are modified via niche construction to produce long-term change, the latter then results in what has been termed ecological inheritance (Odling-Smee 1988;
Odling-Smee and Laland 2012). By this is meant that the next generation literally inherits the modified eco-cultural niche, complete with a new set of ecological selection pressures, from the previous generation, which in turn modifies the fitness values of biological and cultural traits (Odling-Smee and Laland 2012). The concept of ecological inheritance is then perhaps most important here to consider with regards to the spread and development of agriculture and its effects on cultural evolution.
While it has been addressed how niche construction is heuristically valuable, as compared with SET, for the sake of highlighting the reciprocal relationship that exists
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between organisms and environments (Laland and O’Brien 2010; Smith 2007b), the legacy of niche construction in the form of ecological inheritance is more practically valuable in addressing particular evolutionary pathways. Furthermore, the concept of ecological inheritance works particularly well in consideration of the eco-cultural niche. Essentially, as defined by Odling-Smee et al. (2003: 252), ecological inheritance is a third inheritance system that is directed by niche construction. The eco-cultural agricultural niche may therefore also be analyzed as an inheritance system, one which assumes the occurrence of niche construction and encompasses the inheritance of biological, cultural, and ecological traits (Fig. 1).
Figure 1: Eco-cultural niche correlative descent with modification model.
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The suggestion of an eco-cultural niche inheritance system then implies that by tracking change through the eco-cultural niche, we may also discover consequential (vs. non- consequential) change within the other three inheritance systems and elaborate on the role of niche construction in this regard. In other words, the whole can be contained within a correlative descent with modification model (Shennan 2000). The diachronic evaluation of the eco-cultural niche can then aid in determining the impacts of niche construction with reference to change in the relationship between the cultural and ecological setting over time. A thorough analysis of the cultural repertoire as represented by the archaeological record will then provide the necessary information to assess how culture may have produced, responded, or remained indifferent to such shifts in the eco-cultural niche.
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Chapter 3 – Framing the Question The Neolithic (c. 6200 - 4900 BC) in the Struma River Valley cultural diversification and issues of interpretation
3.1 Archaeological Context
Situated in Southwest Bulgaria and Northern Greece (there called Strymon), the Struma
River Valley during the Neolithic Period (c. 6200-4900 BC) served as an important communication artery through which early agricultural practices were spread from the
Near-East and Aegean to Temperate Europe (Grębska-Kulova 2004; Marinova et al. 2012;
Nikolov 2007). The Struma River Valley effectively straddles the Mediterranean and
Continental climatic and vegetational zones, offering a transitional sub-Mediterranean environment that was particularly conducive to the northward adoption of early agricultural domesticates (Marinova 2007). However, a distinctive characteristic of the Struma River
Valley when compared with the regions to the immediate north and south is its ecological heterogeneity, both horizontally along its North-South axis and also vertically, along the gradient of the valley slopes. The latter in turn then begs the question as to how the
Neolithic populations of the region were adapted to this distinctive and localized ecological setting.
For approximately 1300 years, Neolithic agricultural communities gradually settled and multiplied across the fertile terraces of the Struma River Valley (Pernicheva-Perets et al.
2011). Furthermore, occurrences of material culture diversification and evidence of shifting settlement patterns clearly illustrate that the spread of Neolithic lifeways throughout the
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region was fundamentally a dynamic process (Grębska-Kulova 2004). In this chapter, by reviewing the temporal and regional characteristics of the Neolithic in this area, I make the general observation that the regional geographic and climate characteristics of the Struma
River Valley influenced the evolution of Neolithic settlements in the region, from an originally undiversified cultural base in the Early Neolithic to heightened variability between its different sub-regions. As there is evident variability, it then becomes reasonable to ask whether the evolution of cultural variability is at least in part driven by the ecological setting of the Struma River Valley and differentiation in the evolution of the early agricultural niche. By developing and diachronically assessing eco-cultural niche models for the Neolithic Period in the Struma River Valley, we stand not only to determine the ecological constraints within which early agricultural settlements were distributed, but we may also elaborate on the role of culture and human adaptability in mitigating those constraints over time via niche construction. Additionally, and as the previous chapter outlined, niche construction may permanently alter natural selection pressures resulting in eco-cultural niche inheritance, while the latter also impacts evolutionary processes. Thus, correlations between eco-cultural niche inheritance and culture change may also be advanced when applicable.
Before any such investigation can be undertaken, however, it is first necessary to become acquainted with the geographic and archaeological specifics of the area in order to adequately define the study region. This chapter then summarizes the landscape and climate characteristics of the Struma River Valley, provides an introduction to the Neolithic chrono-cultural periodization system, and presents some indications on subsistence practices collectively derived from faunal and paleobotanical investigations.
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3.2 Landscape and climate
3.2.1 Geography of the Struma River Valley
The Struma River Valley encompasses the greater portion of Southwest Bulgaria and also includes Central and East Greek Macedonia (Fig. 2). The Struma River runs 415 km long, beginning at its source on the southern slopes of Vitosha Mountain on the outskirts of the
Bulgarian capital of Sofia and ending at its outflow at Orphanos Bay in the Aegean Sea
(Zagorchev 2007). To the east rise the Rila and Pirin massifs (the former recorded as the highest peak in the Balkan Peninsula) while to the west lay the more gradual Osogovo,
Ograzhden, Maleshevska, and Belasitsa ranges (Zagorchev 2007). Despite its geographic characterization as being situated between a series of imposing mountains, however, the terrain is also punctuated by a series of low-lying passes and conjoining river valleys. The
Struma River Valley is then also intermittently linked with all of its neighbouring regions.
These include the Vardar/Axios Valley to the west, the Mesta/Nestos Valley to the east, the
Sofia Basin to the north, the region of West Greek Macedonia to the southwest, and with
Turkish and Aegean Thrace to the southeast. Overall, The Struma River Valley comprises a total catchment area of approximately 18 000 km2.
The Struma River largely reached its present course during the Middle to Late
Pleistocene—781 to 126 kya—when episodes of tectonic uplift and climate change caused significant drainage basin deviations as well as alternating periods of fluvial incision and aggradation (Zagorchev 2007). The latter geomorphological processes led to the formation of large gorges and the step-like sequence of river terraces that are still today prominently featured throughout much of the Struma River Valley (Zagorchev 2007). Furthermore,
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these geomorphological processes also shaped the valley into several distinct basins
(Zagorchev 2007). Based on this natural compartmentalization of the terrain, the Struma
River Valley may then be further divided into three defined sub-regions: the Upper, Middle, and Lower Struma Valleys.
The Upper Struma Valley lies in the north, is delimited by the Sofia Plain to the Western
Balkan Mountains, and is composed of four sub-basins—the Pernik, Radomir, Kyustendil, and Boboshevo Basins—each in turn delimited by a gorge (Pernicheva-Perets et al. 2011).
The Middle Struma Valley lies in the center of the region and is composed of three sub- basins—the Blagoevgrad, Simitli, and Sandanski-Petrich Basins. It is divided by the Kresna
Gorge—an especially worthy landmark of consideration. Reaching 16 km in length, it is the longest gorge in the Struma River Valley and also formally marks the transitional border between the Mediterranean and Continental climatic and vegetational zones (Pernicheva-
Perets et al. 2011). Lastly, the Lower Struma Valley begins at Rupelski Gorge in the south where the river enters Central Greek Macedonia and forms the wide Serres Lowlands. The
Struma River then joins with the Angitis River—as the latter descends from the Drama
Basin—before outflowing at Orphanos Bay into the Aegean Sea.
With regards to the Aegean Sea, the effects of changing sea level must also be considered as having impacted the geography of the Struma River Valley. The results of several investigations directly concerning relative sea-level change in the Northeast Aegean demonstrate that sea-level has been consistently rising since the Last Glacial Maximum some 18 thousand years ago (Lambeck and Purcell 2005; Pavlopoulos 2012; Vacchi et al.
2014). Furthermore, each of these studies determined that since the beginning of the marine
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transgression, sea-level has never been higher than at present. The implications of the latter statement are two-fold. First, it implies that at no time during the Neolithic Period was the current region defined as the Lower Struma Valley fully or even partially covered by the
Aegean Sea. Second, and most importantly, it does imply that much of the former coastal area is today submerged below sea-level, therefore masking any evidence of potential
Neolithic habitation.
Figure 2: The Struma River Valley.
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3.2.2 Climate characteristics
The spread of early agriculture from the Near-East and Mediterranean to Continental climatic and vegetational zones has been repeatedly associated with the 6200 cal BC climate change event, which modified environmental conditions throughout most if not all of the Northern Hemisphere (Berger and Guilaine 2009; Pross et al. 2009; Weninger et al.
2006). In fact, a thorough investigation undertaken by Weninger et al. (2006) has sufficiently demonstrated a chronological association between the appearances of Early
Neolithic settlements in Continental Europe with that of the 6200 cal BC event. The latter resulted in increased aridity in much of the Near-East, to wetter and cooler conditions in
Continental Europe, and in general instances of climatic irregularity occurring throughout the North Mediterranean (Berger and Guilaine 2009). Considering that the Struma River
Valley is situated directly between two of the identified climate change regions (namely, between Continental Europe and the North Mediterranean) it then follows that climate conditions would have varied significantly from north to south during the Neolithic Period.
In the Upper and Middle Struma Valleys, temperatures around 6000 cal BC would have only been slightly colder than today during the summer periods and almost at present levels during the winter (Marinova 2007). Furthermore, Davis et al. (2003) have determined based on pollen-climate reconstructions that from 6000 BC onwards, temperatures in Southern
Europe have been generally maintained almost at present day levels. Annual precipitation in the lowlands ranges from 600 mm in the Upper Struma Valley to 780 mm in the Middle
Struma Valley, while mean annual temperatures range from 10 °C in the Upper Struma
Valley to 14 °C in the Middle Struma Valley (Marinova et al. 2012). Both sub-regions are
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generally characterized by a cold climate as compared with most of the Mediterranean, with winter frosts and extended periods of below 0 temperatures (Marinova 2007). High temperature ranges and moderate precipitation seasonality with slightly increased winter precipitation is therefore the norm, however, with some important differences in the overall ecological conditions between the Upper and Middle Struma Valleys, respectively. In terms of the vegetation cover, in the lowland areas where Neolithic sites have been located, xerothermic oak forests expanded over the landscape and sub-Mediterranean floral elements—identified by the presence of hazel and oriental hornbeam, among other such species—increase in abundance as one travels from north to south (Marinova et al. 2012;
Marinova 2007; Stefanova and Ammann 2003; Tonkov 2003).
In the Lower Struma Valley, the situation is markedly different and is defined by climatic irregularities beginning with the 6200 cal BC event. Pollen sequences retrieved from the
Tenaghi-Philippon peatlands in the Drama basin of East Greek Macedonia serve as a direct proxy to past climate conditions in the Lower Struma Valley (Peyron et al. 2011; Pross et al. 2009; Pross et al. 2015). At the onset of the 6200 cal BC event—in contrast with the
Upper and Middle Struma Valleys—the pollen record bears witness to partial deforestation with the retreat of thermophilous and evergreen species giving way to steppe-like vegetational elements (Pross et al. 2009). Oak was however not so severely affected (Pross et al. 2015). Such an event suggests colder than usual winters, the occurrence of frost, as well as a marked increase in temperature seasonality (Pross et al. 2009).
Precipitation dropped in the Lower Struma Valley from 800 to 600 mm per annum, with a decrease in winter precipitation and an increase in summer precipitation (Pross et al.
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2015). Overall, the region may be characterized by marked precipitation seasonality and a low contrast in temperature (Peyron et al. 2011; Pross et al. 2015). The Lower Struma
Valley also exhibits reversed precipitation seasonality when compared with the Upper and
Middle Struma Valleys, having dry winters and relatively wetter summers. The colder climate and marked seasonality attested in the Lower Struma Valley as compared with the rest of the Aegean coast at that time has been tentatively explained by the influence of mesoclimatic factors and by its increased susceptibility to the Siberian High (Pross et al.
2015). Although there is a slow recovery of the forest vegetation alongside a decrease in steppe like elements following the 6200 cal BC event, from 5800 cal BC onwards a general aridification trend commences with renewed decreases in winter precipitation and increases in summer precipitation until arriving at present day values (Peyron et al. 2011).
The geographic North-South gradient of the Struma River Valley, with the Kresna Gorge at its epicenter, thereby exemplifies latitudinal climatic and vegetational differentiation.
Overall, loosely defined climate zones can be associated to each of its sub-regions.
Although modern anthropogenic impacts have today modified the floral characteristics of the region, and while temperature and precipitation values are slightly different when compared with the past, the relative contrast between each of the Struma River Valley’s sub-regions in terms of climate and terrain remains very much the same at present.
3.3 The Neolithic chrono-cultural periodization system
Considering each of its sub-regions, one hundred and seventeen distinct settlements from the Neolithic Period have been identified in the Struma River Valley. However, a notable
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complication exists regarding the chrono-cultural periodization system of the region
(Pernicheva-Perets et al. 2011; Tsirtsoni 2016). Issues regarding the chronological placement of settlements along a comparable absolute time-scale arise mainly because the characteristic finds of the Neolithic are not evenly distributed across the entire valley, nor are they wholly isolated to the Struma River Valley alone, further emphasizing the importance of geographic connections with the neighbouring regions. In most cases, the characteristic elements of Neolithic culture in the Struma River Valley have also been found geographically and chronologically distributed in parts of Eastern Bulgaria, the
Republic of Macedonia, Serbia, Turkish and Aegean Thrace, as well as Mainland Greece
(Demoule 2009; Pernicheva-Perets et al. 2011; Tsirtsoni 2016). Furthermore, very different chronological periodization systems are in use for each of the regions in question complicating any attempt at a supra-regional synthesis (Pernicheva-Perets et al. 2011;
Tsirtsoni 2016).
For the purposes of this study, a variant of the periodization system first suggested by
Georgiev (1961)—with regards to the stratigraphy at Tell Karanovo in Eastern Bulgaria— and later adopted by Pernicheva (1995; 2007) in relation to the Middle Struma River Valley will be utilized (Table 1). Due to the very limited number of radiocarbon dates for the region in general, the periodization system is primarily defined by the detailed sequencing of pottery types and in their association across settlements (Pernicheva 1995; 2007). All absolute dates reported here are based on Boyadziev (Table 2; 1995; 2007).
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Table 1: Chrono-cultural periodization system; after Perničeva 2007.
Table 2: Absolute date ranges for the Bulgarian Neolithic; after Boyadziev 1995.
3.3.1 The Early Neolithic (6200 - 5450 cal BC)
In total, thirty-three settlements represent the Early Neolithic Period in the Struma River
Valley (Fig. 3). Notably, not a single Early Neolithic settlement has been discovered in the
Lower Struma Valley (Demoule and Perlès 1993; Perlès 2001; Pernicheva 1995;
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Pernicheva-Perets et al. 2011). All throughout the Early Neolithic Period, the location of settlements generally appears to remain the same in character as they are situated along the first and/or second terraces of the Struma River and its principal tributaries (Pernicheva-
Perets et al. 2011). In terms of settlement patterns, no significant difference is immediately noted between the first (6200-5900 cal BC) and second (5900-5450 cal BC) half of the
Early Neolithic. The Kresna Gorge, however, did act as a cultural barrier from as early on as 5900 cal BC mitigating the diversification of material culture.
From a typological point of view, the settlement of Krainitsi in the Upper Struma Valley represents the oldest known phase of the Early Neolithic, comprising a monochrome ceramic stage that parallels that of the earliest Neolithic in Thessaly (Čohadžiev 1998). To this point in time, it is the only known settlement that provides evidence for such an early stage of development in the region (Čohadžiev 1998). During the first half of the Early
Neolithic (c. 6200 - 5900 cal BC), following the monochrome stage—as evidenced also by the stratigraphy at Krainitsi—a white on red painted ceramic tradition emerges near homogeneously across the Middle and Upper Struma Valleys (Pernicheva 1995;
Pernicheva-Perets et al. 2011). During the second half of the Early Neolithic (c. 5900 -
5450 cal BC), north of Kresna Gorge a dark on red painted ceramic tradition (i.e. classic
Starčevo), having close affiliates in the Vardar Valley (see Anza; Gimbutas 1974), progressively supplants the white on red painted tradition (Pernicheva 1995; Pernicheva-
Perets et al. 2011). However, the white on red painted tradition continued to persist to the south of Kresna Gorge directly into the Middle Neolithic Period (Pernicheva 1995;
Pernicheva-Perets et al. 2011). Material culture diversification was thus possibly mitigated
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Figure 3: Early Neolithic settlements.
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by eco-cultural terms as early on as the second half of the Early Neolithic.
3.3.2 The Middle Neolithic (5450 - 5200 cal BC)
Across the entire Struma River Valley forty-two settlements have been recorded for the
Middle Neolithic Period (Fig. 4). Overall, there is a reduction in the number of sites attributed to this cultural phase in the Upper Struma Valley alongside a rapid new proliferation of settlements in the Middle and Lower Struma Valleys (Pernicheva-Perets et al. 2011). In all but one case, each of the Middle Neolithic settlements found in the Upper
Struma Valley are situated in the same locations (barring the occurrence of slight horizontal stratigraphic shifts) as settlements that were occupied during the Early Neolithic, though no distinct cultural horizons have been noted. In the Middle Struma Valley, however, two
Early Neolithic settlements appear to have been abandoned (i.e. Brezhani and Pepelnikov
Chukar) while Middle Neolithic horizons are found at all the same locations as the remaining Early Neolithic sites and new settlement clusters also emerge. In the Lower
Struma Valley, settlements here emerge for the first time during the Middle Neolithic
Period (Pernicheva-Perets et al. 2011).
The Middle Neolithic Period is uniformly characterized by black polished pottery and emphasized bi-conical shapes (Pernicheva 1995; Pernicheva-Perets et al. 2011). In some instances, these black polished bi-conical ceramics are also decorated in the Dolna-Ribnitsa style—dual parallel punctate lines above the carination, or more rarely a single punctate line—however, this decorative technique does not occur at settlements in the Upper Struma
Valley, where vertical grooving and channeling instead is more prevalent above the
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carination (Pernicheva-Perets et al. 2011). In the Upper Struma Valley, Middle Neolithic settlements (n=11) are represented by less than half in comparison with their Early
Neolithic counterparts (n=24) (Pernicheva-Perets et al. 2011). However, it should be noted that Early Neolithic sites in this region, such as Priboi, Pernik, Galabnik and Divotino, bear evidence of continuous occupation into the Late Neolithic and that the absence of so-called
Middle Neolithic elements does not necessarily imply a chronological hiatus. Rather, it suggests that the elements properly recognized as Middle Neolithic in the Middle and
Lower Struma Valleys may represent an instance of cultural diversification that did not fully penetrate the more northern reaches of the Valley, as is also there evidenced by the absence of the Dolna-Ribnitsa style.
In the Middle Struma Valley, the situation is markedly different. Twenty-one settlements from the Middle Neolithic Period have there been recorded, seven of which are situated stratigraphically above the preceding Early Neolithic settlements (Pernicheva-Perets et al.
2011). The remainder and majority (n=14) are located over previously uninhabited terrain in the lower foothills of the Ograzhden and Pirin mountains (Pernicheva-Perets et al. 2011).
In the Lower Struma Valley, on the other hand, all Middle Neolithic settlements (n=10) are located in the Drama Basin over previously uninhabited terrain as no Early Neolithic settlements to date have been found in the region. Problematically, the earliest Middle
Neolithic layers from sites in the Lower Struma Valley also contain a ceramic variant that is more typical of the Late Neolithic Period (i.e. black-topped ceramics), and thus may in fact represent a later chronological stage of development (Pernicheva-Perets et al. 2011).
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Figure 4: Middle Neolithic settlements.
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Therefore, it has been argued that most of these are likely to have been occupied rather towards the Middle to Late Neolithic transition. The sudden and substantial presence of
Middle Neolithic type settlements in the Middle Struma Valley and their comparatively late development in the Lower Struma Valley thereby suggests that a more southward oriented settlement pattern progressively developed at this time (Pernicheva-Perets et al.
2011).
3.3.3 The Late Neolithic (5200 – 4900 cal BC)
During the Late Neolithic Period (c. 5200 - 4900 cal BC), the whole Struma River Valley witnesses a general increase in the number of settlements, though the situation differs specifically in all three of its sub-regions (Kulowa and Kulow 2007; Pernicheva-Perets et al. 2011). The total number of settlements doubles from just forty-two in the previous period, now reaching eighty-eight in total (Fig. 5). Furthermore, fifty-eight of the eighty- eight Late Neolithic settlements are situated over previously uninhabited terrain and are first occupied only during this period (Pernicheva-Perets et al. 2011). In the Upper Struma
Valley there are twenty-two Late Neolithic settlements, in the Middle Struma Valley there are twenty-six, and in the Lower Struma Valley there are forty. In the Upper Struma Valley, the number of settlements is actually reduced as compared with the Early Neolithic Period, the number of settlements increases by five in the Middle Struma Valley between the
Middle and Late Neolithic Periods, and the Lower Struma Valley exhibits a drastic increase with the appearance of thirty new settlements at this time. With regards to settlement patterns, there is now a noticeable distinction between their types and locations. Some
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settlements begin occupying vast areas on the first and/or second terraces of the Struma
River—reaching upwards of 210 000 m2—while others occupy more hilly terrains farther away from the main river systems (Pernicheva-Perets et al. 2011; Genadieva 2007). This general trend applies to all sub-regions.
The period is characterized primarily by the appearance of black-topped ceramics across the entire Struma River Valley. Furthermore, several sub-regional ceramic styles are now also more clearly attested. In the Upper Struma Valley there is a strong Vinča B—Morava variant influence (Grębska-Kulova 2003; Boyadziev 1995; Pernicheva-Perets et al. 2011;
Vajsov 2007). The noticeable Vinča B influence in the Upper Struma Valley may be tentatively associated with the latter’s equally strong affinity with the Classic Starčevo culture during the second half of the Early Neolithic (c. 5900 BC). In the Lower Struma
Valley, the Akropotamos brown on cream painted style becomes the dominant ceramic type followed shortly afterwards—nearing the end of the Late Neolithic—by the Galepsos dark on red painted style (Grębska-Kulova 2003; Bojadžiev 1995; Pernicheva-Perets et al. 2011;
Vajsov 2007). The Akropotamos and Galepsos ceramic styles are by far most prevalent south of Rupelski Gorge, with specimens from the north represented only in minor quantities and mainly as imports (Pernicheva-Perets et al. 2011). In the Middle Struma
Valley, both the Vinča B and Akropotamos styles can be found; however, a local dark on red painted variant of the Akropotamos type named Topolnitsa-Akropotamos there emerges south of Kresna Gorge as the defining characteristic of the Final Late Neolithic
Period. This so-called Topolnitsa-Akropotamos variant appears to be a local imitation of the southern Akropotamos style (Grębska-Kulova 2003; Bojadžiev 1995).
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Figure 5: Late Neolithic settlements.
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Furthermore, in the Middle Struma Valley—to the north of Kresna Gorge—nearing the end of the Late Neolithic Period, it should also be noted that there is the emergence of yet another pottery type found distinctively on hilltop settlements in the Blagoevgrad Basin
(Pernicheva-Perets et al. 2011). The latter pottery type is monochrome grey and produced using perfectly purified clay, with a cement-like structure (Pernicheva-Perets et al. 2011).
Effectively, this latter case marks the end of the Late Neolithic Period as the region then enters the Early Chalcolithic transition (c. 4900 cal BC) (Pernicheva-Perets et al. 2011).
All in all, the Late Neolithic Period can be described as a certain time of dynamic settlement proliferation, expansion, and marked cultural diversification.
3.4 Subsistence Practices
3.4.1 The faunal record
Early Neolithic
At Krainitsi I—the earliest known Neolithic settlement in the Struma River Valley— materials were recovered primarily from pits associated with the monochrome ceramic stage (Čochadžiev et al. 2007). While there is no compelling evidence of architectural plans or settlement layout at this horizon, interpretations made from the faunal assemblage are enlightening. Among the faunal remains studied the minimum number of individuals
(MNI) shows that 87% of the assemblage was composed of domestic animals while only
13% can be attributed to wild fauna. The situation has also been compared with the faunal remains from Kovachevo—the next earliest known site, located in the southern reaches of the Middle Struma Valley—for which similar proportions (85% domestic, and 15% wild)
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have been recorded (Čochadžiev et al. 2007). Additionally, investigations at the Early
Neolithic levels of Mursalevo in the Upper Struma Valley and Ilindentsi in the Middle
Struma Valley also attest to the dominance of domestic over wild animal species (Marinova et al. 2016). Therefore, even at this early stage of the Neolithic, a greater dependence on domestic food sources was well established throughout the region.
In all reported cases, the domestic faunal assemblages during the Early Neolithic are dominated by sheep and goats, while the proportions of pigs and cattle vary in importance between settlements. At Mursalevo, however, the reported proportions according to number of identified specimens (NISP) are sheep/goat 66%, cattle 14%, and pig 19%
(Marinova et al. 2016). The same predominance of pig over cattle is also noted at
Kovachevo during the Early Neolithic Period (Marinova et al. 2016; De Cupere unpublished). Lastly, kill-off patterns at Mursalevo also indicate that young animals were preferentially slaughtered favouring the production of tender meat and leading to the conclusion that secondary animal products were not yet heavily exploited during the Early
Neolithic Period (Marinova et al. 2016). The wild taxa (presumably hunted) at Mursalevo include otter, beaver, goose, swan, wolf, brown bear, fox, hare, red deer, roe deer, fallow deer, wild boar, and aurochs (Marinova et al. 2016).
Middle Neolithic
As of yet, no distinct structural layers have been found or directly attributed to the Middle
Neolithic Period in the Upper Struma Valley. Furthermore, faunal remains recovered from
Middle Neolithic sites in the Middle Struma Valley are unfortunately scarce and seldom
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reported, though the excavations at Ilindentsi II and the continued publications of the investigations at Balgarchevo II and Kovachevo II in part aim to rectify this apparent gap in the literature (Grębska-Kulova, pers. comm.). If the faunal remains reported for the Early
Neolithic phases at Ilindentsi I and Kovachevo I are any indication, one could suppose the continued dominance of domestic fauna. Additionally, no faunal remains have been reported for the eponymous site of Dolna-Ribnitsa, though a suggestion for the prevalence of hunting and stock breeding has been advanced with regards to the geomorphological characteristics of the settlement, as located in the lower foothills of the Ograzhden
Mountain and comparatively farther away from prime agricultural land (Perničeva 1983).
At Sitagroi, first settled during the Middle Neolithic Period in the Lower Struma Valley, the faunal assemblage is comparatively well reported. MNI counts reported for Sitagroi
Phase I have identified a ratio of 90% domestic taxa vs. 10% wild (Bökönyi 1986). Of the domestic taxa, the proportions between goat/sheep, cattle, and pig are 49%, 34%, and 17% respectively (Bökönyi 1986). The author notes the substantially higher proportion of cattle at Sitagroi Phase I as compared with sites of the Early Neolithic Period in West Greek
Macedonia (i.e. Nea Nikomedeia and Argissa Magoula), at which over 70-80% of the domestic assemblage consists of sheep and goat (Bökönyi 1986). The same relative comparisons with regards to the predominance of cattle at Sitagroi I can also be put forward with the Early Neolithic sites found elsewhere in the Struma River Valley, in which cattle occupied a much lower percentage of the domestic assemblage. Of the wild taxa reported, red deer, wild boar, and aurochs occupy the greatest three percentages, while fallow deer, roe deer, badger, wolf, fox, hare, mallard, and other bird species are also present in lesser quantities (Bökönyi 1986).
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Late Neolithic
In the Upper Struma Valley, the faunal record for the Late Neolithic Period is most complete at Mursalevo. At Mursalevo, the number of identified specimens (NISP) indicates an absolute decrease in the exploitation of wild fauna during the Late Neolithic Period with
94% domestic taxa and only 6% wild taxa represented (Marinova et al. 2016). Furthermore, several of the wild taxa represented in the faunal assemblage from the Early Neolithic occupation at the site are no longer found (Marinova et al. 2016). Additionally, the respective percentages of wild boar and red deer decreases while the presence of aurochs seems stable or even slightly increased (Marinova et al. 2016). Of the domestic taxa, sheep and goat occupy 55%, pig 13%, and cattle nearly double in importance making up 32%
(Marinova et al. 2016). Kill-off patterns also demonstrate that domestic sheep/goat and cattle are being kept to greater maturity, indicating the possible exploitation of secondary animal products occurring alongside the increase of cattle in the assemblage (Marinova et al. 2016).
In the Middle Struma Valley, the minimum number of individual count (MNI) at
Promachon-Topolnitsa identifies 73% domestic species and 27% wild taxa (Iliev and
Spassov 2007). Here should be noted the anomalously high proportion of wild taxa.
Absolute proportions between sheep/goat, cattle, and pig are 49%, 39%, and 12% respectively (Iliev and Spassov 2007). Kill off patterns also indicate that the animals were kept to greater maturity and thus also suggests the possible exploitation of secondary animal products (Iliev and Spassov 2007). Furthermore, the relative proportions of cattle size provide evidence at Promachon-Topolnitsa for cross-breeding between at least two
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different variants of cattle, the first being smaller and the second having proportions more closely approximating the wild aurochs (Iliev and Spassov 2007). Their proportions are 8% for the small breed, 69% for the large breed, and 23% are likely hybrids (Iliev and Spassov
2007). At Damyanitsa, also in the Middle Struma Valley, preliminary results show that wild species in contrast to Promachon-Topolnitsa occupy a similar proportion to that of
Mursalevo while the predominance of cattle in the domestic assemblage appears even greater (nearing 75%) than at both Mursalevo and Promachon-Topolnitsa (De Cupere unpublished). At Sitagroi II, in the Lower Struma Valley domestic species occupy 92% while wild species occupy 8% (lower than the previous period), and the proportions of sheep/goat, cattle, and pigs is 49%, 28%, and 23% respectively (Bökönyi 1986).
Considering the wild taxa, the ungulates are now comparatively less well represented at
Sitagroi II (Bökönyi 1986).
3.4.2 Paleobotanical investigations
Early Neolithic
Several investigations have demonstrated a broad and recurring plant use pattern throughout many Early Neolithic sites in the Struma River Valley (Kreuz et al. 2005;
Marinova 2006; Marinova 2009; Popova and Marinova 2007). First, the crop assemblage of the earliest farmers is consistent with that of the Near Eastern crop assemblage (as per
Zohary 1996). The latter consists of chick pea, bitter vetch, lentils, pea, barley, einkorn and emmer wheat, and with the added inclusion of grass pea (Marinova and Valamoti 2014).
Second, the relative proportions of different crops have been associated with local
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differences in environmental conditions, with for instance the prevailing presence of einkorn over emmer wheat on some settlements having likely resulted from the former’s ability to propagate even in adverse ecological conditions and/or soil types (Marinova
2006). In general, however, there appears to be a shift from einkorn having been more prevalent in the first half of the Early Neolithic to the predominance of emmer in the second half, though the situation is not always consistent across settlements (Marinova and Popova
2007). Hulled barley also played an important role during the Early Neolithic, often representing the second greatest crop quantity in comparison to wheat (proportion of 1:3 -
1:6; Marinova 2006). Hulled barley also possesses the ability to withstand adverse ecological conditions and its relative proportions may have varied from site to site also in that respect (Marinova 2006). A thorough analysis of the weed assemblage confirms that both winter and summer crops were sown (Kreuz et al. 2005). Finally, the various legumes offer good sources of protein, as does grass pea, which may have been used to mitigate the difficulties associated with obtaining adequate protein levels from domestic animals during the early development of the Neolithic in the region (Marinova and Popova 2007).
With regards to wild flora, the predominance of oak is noted in the construction of dwellings, while riparian woodland elements were also used for wattle (Marinova 2009;
Marinova and Thiebault 2008). The notable presence of wild fruit species in some of the settlements, and most especially at Kovachevo, indicates that the Neolithic inhabitants also made good use of wild resources when available (Marinova 2006; Marinova 2009). At
Kovachevo, these included cornelian cherry, plum, and wild grapes (Marinova and
Thiebault 2008). Their limited identification during the Neolithic in general, however, has been associated with inconsistencies in regard to the collection methods utilized during
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investigation rather than as evidence for their absence (Marinova 2009). The collection of oak and riparian woodland species used in the construction of buildings may also have unintentionally opened up areas of undergrowth along the forest edges in which such wild fruit species could have more easily grown and been obtained (Marinova and Thiebault
2008). Furthermore, the presence of wild floral species at Kovachevo increases along with the continued Early Neolithic occupation of the settlement (from Kovachevo Ia to Id), and thus also along with the intensified use of woodland resources for construction purposes
(Marinova and Thiebault 2008). A similarly widespread use of wild resources (cornelian cherry, dogwood, hazel, common fig, strawberry, apple, pear, plum, dewberry, black elder, grapes, and water chestnut) is also reported at Mursalevo and is indicative of several different types of ecological settings having been targeted for harvest (Marinova et al.
2016).
Middle Neolithic
Publications regarding the paleobotanical record for the Middle Neolithic Period in the
Middle Struma Valley, like those of the faunal record, unfortunately remain scarce. The following discussion is thus necessarily limited to the information retrieved from Sitagroi
I. The charcoal assemblage identifies oak, ash fraxinus, chestnut, rockrose, and snowbell in the construction of dwellings, which is consistent with the known climate and vegetation in the Lower Struma Valley at that time (Rackham 1986). The main crops recovered from
Sitagroi I include einkorn, emmer, hulled barley, bitter vetch, pea, and oats (Renfrew 2003).
The most common of the crops was einkorn (Renfrew 2003). The latter is found in all cases
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in the form of threshed grain (Renfrew 2003). Emmer, on the other hand, represents the second most important crop type, though it was found in association with several husks and spikelets indicating that the latter was not always immediately threshed (Renfrew 2003).
Hulled barley is found mixed with other crop types, including both einkorn and emmer, suggesting its status as a secondary crop and the possibility that crops were also grown in maslins (i.e. mixed crop fields; Renfrew 2003). Bitter vetch makes up the most substantial pulse crop, while oat—although present—appeared in very minor quantities and is interpreted as a weed because its wild form may also be found in the study region (Renfrew
2003). Of the wild flora, cornelian cherry, pistachios, and a single almond husk have been reported (Renfrew 2003).
Late Neolithic
Generally, during the Late Neolithic Period the continued use of all the previous crop types is observed. Naked barley, however, increases in importance within the Struma River
Valley at this time (Marinova 2007). At Mursalevo, in the Upper Struma Valley, it is interesting to note that the proportions of einkorn and emmer wheat shift from a less clear distinction during the Early Neolithic Period to the clear predominance of einkorn over emmer wheat in the Late Neolithic Period (Marinova et al. 2016). The same shift to the predominance of einkorn is noted for most of the Late Neolithic settlements studied in the region (Marinova 2007). Additionally, new domestic taxa now appear at several settlements, but in very minor quantities—Panicum milliaceum at Drenkovo-Ploshteko
(Marinova and Popova 2007); Triticum aestivum at Sitagroi II (Renfrew 2003); “new”
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wheat, Triticum aestivum, and Triticum durum at Promachon-Topolnitsa (Valamoti 2007).
The importance of the pea also increases at Mursalevo (Marinova et al. 2016). Both peas and einkorn are reliable crops in adverse growing conditions (Marinova et al. 2016).
Overall, the presence of wild floral remains at Mursalevo significantly decreases in the Late
Neolithic Period (Marinova et al. 2016).
Additional evidence from Promachon-Topolnitsa in the Middle Struma Valley suggests that emmer, einkorn, and barley were concomitantly grown either as single crop stands or as maslins (i.e. mixed crop fields) and flax is now also found in minor quantities (Valamoti
2007). The evidence from weeds recovered in the crop assemblage of Southwest Bulgaria generally also indicates the continued sowing of both winter and summer crops at this time
(Kreuz et al. 2005). In the Lower Struma Valley, einkorn continues to be the predominant crop type at Sitagroi II and lentils are now the most abundant pulse (Renfrew 2003). Barley, bitter vetch, and peas continue to be of relative secondary importance (Renfrew 2003). Of the wild species, cornelian cherry, almond, and wild grape are again represented (Renfrew
2003). Also of note is the wild grape stores recovered from Dikili Tash during the Late
Neolithic Period (Valamoti 2015).
3.5 Was the spread of Neolithic settlement across the Struma River Valley an adaptive expansion?
The diversified geographic and climate characteristics of the Struma River Valley appear to have impacted the process of cultural evolution during the Neolithic. For instance, some differences could be noted in the composition of faunal and crop assemblages from one
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stage of the Neolithic to the next—the proportion of cattle steadily increases over time reaching a maximum in the Late Neolithic and there is also a clear predominance of einkorn over emmer wheat at that time—occurring alongside an extension of settlement.
Furthermore, during the Late Neolithic three clearly defined cultural styles emerge near exclusively in each of the Struma River Valley’s sub-regions, which can reasonably be hypothesized to have occurred from local adaptations to specific types of microclimates within the valley setting. Considering that loosely defined climate zones may also be attributed to each of the Struma River Valley’s sub-regions, it is arguable that changes associated with the various stages of the Neolithic then might also be related to differences in eco-cultural niche inheritance. Geography and climate alone, however, should not be immediately invoked as causal factors. Cultural and historical contingencies are also made apparent from a diachronic point of view, in that the distribution of Early and Middle
Neolithic cultural groups appears less restricted in geographic terms, or at least not in their initial and final stages, respectively. Whether or not the specific eco-cultural niche of each population precluded them from also occupying other ecological zones nonetheless remains to be determined. That is to say, by determining whether or not each population’s eco- cultural niche is exclusive, partially overlapping, or identical with those preceding, following, or co-existing may shed light on the nature of these apparent cultural divisions and also to elaborate on cultural change in that regard.
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Chapter 4 – Data and Methods Settlement, environment, and eco-cultural niche modeling
4.1 Considerations in eco-cultural niche modeling
Eco-cultural niche modeling involves calculating the environmental space (i.e. in reference to the geographic distribution of ecological variables) within which a particular set of cultural traits, such as human settlements, exist. This is no simple task and a number of probable contingencies need to be resolved, themselves dependent upon the specifics of the research context (for an overview on the problems and considerations of ecological niche modeling more generally see Peterson 2011). The goal of this chapter is to review the analytical framework and data requirements for undertaking modeling work of this kind.
4.1.1 Developing the modeling framework
The specific research question is the identification of whether there are changes to the eco- cultural niche during the Neolithic of the Struma River Valley. First, there is a need to determine a well-defined archaeological population for which the eco-cultural niche may be identified. An archaeological population, for instance, may be defined based on particular similarities in the cultural material assemblage. Second, the ecological variables used in the modeling process must be carefully selected so as to adequately characterize the relevant eco-cultural conditions. Third, a suitable niche modeling algorithm paired with an appropriate set of evaluation metrics are needed in order to produce reliable results. And
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fourth, seeing as how the ultimate aim is to produce a diachronic assessment of change to the eco-cultural niche, some inter-model statistics for interpretation must be identified.
4.1.2 Setting the diachronic schema
Regarding the diachronic schema, an important set of problems and considerations becomes apparent. For one, it is necessary to decide what constitutes a reasonable time interval within which changes to the eco-cultural niche can be identified. In archaeology, instances of cultural change are often highlighted by heuristically defined phases and/or periods. Such phases and/or periods are typically used to represent a diachronic change of characteristics in the cultural assemblage—such as a change in ceramic type—and as such are also said to be indicative of cultural evolution. Therefore, by constructing eco-cultural niche models based on an archaeological population that is also divided into distinct chronological periods a diachronic schema can be established. That is not to suggest that change does not also occur within each individual period, or that the eco-cultural niche changes in every instance of cultural change, but rather that the broad scale changes made apparent by heuristically defined archaeological periods may be more readily assessed and potentially characterized as the cumulative result of finer scale changes that occurred within each individual period. The assumption is that the same scenario then may also hold true with regards to change in the eco-cultural niche.
Another important consideration for the construction of a diachronic schema regards change within the ecological setting itself. For instance, climate and terrain are fundamentally dynamic variables that do not always remain stable over long periods of
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time. Unfortunately, such detailed diachronic ecological datasets often do not exist and as such cannot be included within the modeling process. Archaeological research, however, has provided some insights into how environmental and geomorphological conditions have changed over time in the Struma River Valley. Therefore, while the modeling process may need to utilize static ecological datasets for the purposes of the modeling procedure, the outputs of the modeling procedure may be subsequently interpreted in light of known archaeological information elaborating on diachronic ecological change.
The establishment of such a diachronic schema for the construction of eco-cultural niche models then should invariably be featured at the forefront of the data collection process and in the assessment of any potential methodological approaches.
4.2 Data: archaeological settlements
4.2.1 Defining the archaeological population
In terms of defining the archaeological population for the purposes of a diachronic evaluation, it is here suggested that an eco-cultural niche modeling approach based on the geographic locations of archaeological settlements is both suitable and most appropriate
(similar to Banks et al. 2013). By establishing a degree of commonality with respect to their overall material culture, different archaeological settlements may be attributed to a specifically defined archaeological population and divided into relevant chronological periods. Furthermore, as previously mentioned, the chronological division of the population into different archaeologically defined periods also sets up the diachronic schema.
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Therefore, the locations of archaeological settlements pertaining to a specific archaeological population and period are here fundamentally interpreted as eco-cultural expressions by virtue of the fact that archaeological settlements are culturally distributed within ecological space. Not only does such an approach maximize the total number of cultural traits made available for the final diachronic assessment of the niche models by not limiting the composition of the population to a single cultural trait, but it also minimizes the likelihood of producing too generalized models that risk subsuming the total culturally adaptive repertoires of different archaeological populations into a single unified eco- cultural niche model. The latter point is critically important considering that the primary goal is to assess the relationship between evolution and niche construction to changes in the eco-cultural niche. Limiting the production of models to such well archaeologically defined populations then should also serve to regulate any potential issues regarding geographic scope.
4.2.2 Neolithic settlements in the Struma River Valley
As introduced in Chapter 3, a series of intensive archaeological surveys have succeeded in identifying an impressive record of Neolithic settlements in the Struma River Valley. In total, I estimate that more than 80% of the study region has been adequately investigated via land reconnaissance methods (Grębska-Kulova, pers. comm.). Furthermore, each settlement has been associated to a specific archaeological population and period according to Pernicheva’s (1995) relative periodization system (Chapter 3; see also Pernicheva-Perets et al. 2011). Planned using diverse methodologies, sampling biases with regards to the
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known locations of archaeological settlements have been minimized given the broad scope and undertaking of each survey. First, I identified the Neolithic sites used in this study from various primary sources (see Chohadziev 2007, Perničeva 1983, Pernicheva-Perets et al.
2011, Renfrew et al. 1986, Гребска-Кулова 2009; Koukouli-Chryssanthaki et al. 2008) and classified them by relevant period. Second, I established the absolute coordinates of all the settlements via a rigorous review of published maps and archaeological site registries located within the relevant regional museums. The location of each archaeological site was then digitized in ArcGIS 10.3.1. In total, I identified 33 Early Neolithic, 42 Middle
Neolithic, and 88 Late Neolithic settlements for use in the construction of the eco-cultural niche models (Table 3). Furthermore, two Late Neolithic subsets were also produced in association with settlements presenting evidence of Vinča B influence (n=31) and/or cultural markers pertaining to the joint Topolnitsa/Akropotamos style (n=23).
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Table 3: Archaeological settlements by chrono-cultural attribution.
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4.3 Data: ecological variables
4.3.1 Assessing the relevance and availability of ecological variables
With regards to the assessment of ecological variables, a double consideration must be made. First, it can be reasonably assumed that certain ecological variables are more likely than others to influence a community in its choice of settlement location—e.g., access to tillable soils is expected to have been more important for locating an agricultural community than minimizing exposure, which is likely to have been more important for hunter-gatherers. The primary selection of relevant ecological variables can be made, for instance, based on known prior information related to subsistence strategies, such as temperature, soils, and precipitation being inherently related either directly or indirectly to issues of agricultural production. Additionally, one might reasonably suppose that factors related to terrain and/or landcover might also limit the types of spaces suitable for agriculture based settlement. Second, the availability and resolution of suitable ecological datasets has to be determined. A variable might well be relevant to the question at hand, but if there is not enough information on that variable or if obtaining the necessary information is unreasonably arduous and/or time consuming, it cannot be utilized to its full potential. Furthermore, even if information on a particular environmental variable should be made available, one must also consider the resolution of the datasets in reference to the size of the study region. A 10 km2 resolution, for example, would not be suitable in distinguishing fine-grained differences within ecological space, while a resolution of 10 m2 is often too limiting and may mask more important regional considerations. Therefore, a balance should ideally be reached between the resolution of the datasets and the scale of
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the study region.
4.3.2 Characterizing the ecological setting of the Struma River Valley
In total, I selected ten terrain and bioclimatic variables for the analyses as bearing probable relevance for the location selection of early agricultural settlements in the Struma River
Valley (Table 4). These are elevation above sea level, terrain slope, terrain ruggedness index, topographic wetness index, soil typological unit, annual mean temperature, temperature annual range, temperature seasonality, annual precipitation, and precipitation seasonality, which are depicted in Figure 6. I selected these firstly based on their straightforward affiliation to issues regarding agricultural production, and secondly based on their resolution and ease of availability. The terrain variables collectively provide information on the physical setting of the Struma River Valley with regards to both space and suitability for the construction of sedentary agricultural settlements, while the bioclimatic variables may be found to regulate agricultural production in a more biological sense, perhaps leading towards favoring particular crop assemblages or herd compositions, due to their impacts on the length of the growing season and/or in influencing the hydrological setting.
The terrain variables were all computed and derived in ArcGIS 10.3.1 from the Version
2 ASTER Global Digital Elevation Model (Aster GDEM v2; asterweb.jpl.nasa.gov). The
European Soils Database provided evidence on the agricultural suitability and spatial distribution of different soil types, and the bioclimatic variables were freely obtained from the WorldClim present day bioclimatic dataset (Worldclim.org). I used modern bioclimatic
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variables as the chronological range of the Neolithic in the Struma River Valley because I estimated that present day bioclimatic estimates are on average generally closer in value to the interval of the 6200 - 4900 BC period (see Davis et al. 2003) than are other similar bioclimatic datasets also provided by WorldClim. The bioclimatic variables were resampled from an approximate 1 km2 spatial resolution to 729 m2 in order to match the spatial resolution of the terrain datasets. Furthermore, as previously addressed, it should be noted that in assuming static bioclimatic, terrain, and landcover variables in accordance with present day estimates, the influences of known climatic and geomorphological shifts are unavoidably masked and care should be taken when interpreting the significance of the final results.
Table 4: Independent environmental variables.
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Figure 6: Independent environmental variables.
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4.4 Methodological approach
4.4.1 Pearson’s test for statistical collinearity
Following the collection and GIS preparation of the relevant datasets, the first method in the eco-cultural niche modeling process involves checking for collinearity between the chosen ecological variables. Statistical collinearity is defined as a ridged correlation occurring between the values of two or more variables. In other words, the values of two or more variables may be found to linearly predict one another and in fact could represent different expressions of the same general ecological condition. A common example of ecological collinearity, for instance, is the linear relationship often observed between elevation above sea level and temperature values—as elevation increases the temperature decreases proportionately, and as elevation decreases the temperature increases proportionately. It is then critically important to account for such instances of collinearity so as not to introduce a modeling bias and unintentionally favour collinearly related sets of variables in defining the eco-cultural niche. Such instances of collinearity are best dealt with in the eco-cultural niche modeling process by excluding one or more of the collinearly related ecological variables from the analysis (Peterson 2011). Continuous variables should be paired and their scatterplots/histograms examined to determine their Pearson product- moment correlation coefficient (R2)—a measure of linear dependence—to identify instances of collinearity. Should the Pearson product-moment correlation coefficient (R2) be greater than 0.8, one or more of the collinear independent variables is removed from the analysis. The removal of such collinearly related covariates should however be accomplished while bearing in mind the preservation of as much relevant information on
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the total ecological variability of the study region as possible.
4.4.2 Selecting the modeling algorithm: Maxent
Once all of the necessary criteria related to the specifics of the research question have been taken into account and the relevant datasets prepared, a suitable eco-cultural niche modeling algorithm must be selected for use in modeling the relationship between the locations of archaeological settlements and the chosen ecological variables. Maximum entropy species distribution modeling (Maxent) in particular lends itself quite well to such tasks (see Galletti et al. 2013; Conolly et al 2012; Banks et al. 2013). Developed by Phillips,
Dudik, and Schapire (2006; 2008), Maxent’s intuitive interface and readily understandable outputs have already proven an invaluable tool in a number of varied applications with regards to ecological niche modeling more generally (see Anderson and Raza 2010; Elith et al. 2010; Warren et al. 2008). Furthermore, there exists a substantial body of literature on Maxent and its performance has generally been highly acclaimed while statistics packages have also been developed specifically with regards to evaluating and interpreting the results of the Maxent algorithm.
Maxent utilizes presence only data in order to assess the distribution of occurrence points across ecological space. Given that we very rarely (if ever) have reliable absence data in relation to the locations of archaeological settlements, the presence only procedure utilized by Maxent is preferred given the current state of archaeological research. The Maxent modeling algorithm essentially ascertains and graphically represents the relationship between a binary categorical dependent (y)—the presence or pseudo-absence of an
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archaeological settlement—to a set of independent ecological variables (x), so as to identify if and how the independent variables act as predictors in determining the value of the dependent. In this case, the categorical dependent is the presence (value = 1) or pseudo- absence (value = 0) of a Neolithic archaeological settlement. In this application, the independent variables are the terrain and bioclimatic datasets representing the ecological setting of the Struma River Valley (i.e. temperature, precipitation, terrain roughness, etc.) that may be found to contribute to the formulation of the eco-cultural niche.
As a presence-only method, Maxent samples a restricted background to generate a random set of pseudo-absences from which to assess the distribution of the independent variables. The geographic extent of the background area from which the pseudo-absences are sampled should therefore encompass the entire site catchment area and also include a significant portion of the surrounding region in order to capture the total ecological variability of the landscape. A relatively broad boundary should be intentionally selected so as not to restrict the model too severely and risk overfit. However, it is also generally recommended to constrain the borders of the background area to the spatial limits of the presences sample so as not to introduce a spatial sampling bias in the final results (Anderson and Raza 2010). Considering that all of the presence samples are located and well dispersed within the established geographic boundaries of the Struma River Valley, the background area used in the modeling procedure then consists of the entire study-region and parts of the surrounding areas accounting for a total surface of approximately 38,000 km2.
While the default settings of Maxent recommend sampling 10,000 pseudo-absences from the background, the latter is mostly dependent on the absolute size of the study region as
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well as on the available sample size of archaeological settlements. The size of the study- region amounts to 38,000 km2 while the total number of settlements per archaeological period never exceeds eighty-eight. A reduction in the default suggested sample size of pseudo-absences is then required in order to avoid total background saturation and consequently also of model over fit. In this regard, Barbet-Massin et al. (2012) determined that for Generalized Linear Models (GLMs: a statistical procedure similar to that of
Maxent), the increase in accuracy of the model reaches an asymptote when the number of presences is equal to 10% or less of the number of pseudo-absences. Therefore, given the relatively small sample size of archaeological settlements in the Struma River Valley and the size of their associated background area, I modified the parameters of the modeling procedure to meet the criteria as outlined by Barbet-Massin et al. (2012), allowing for the utilization of a reduced pseudo-absences dataset. Specifically, I changed the functional parameters of Maxent from their default setting to sample only 1,000 pseudo-absences (as opposed to the default 10,000).
Maxent uses a defined percentage of the presences (i.e. archaeological settlements) in training the algorithm to determine the value range of the ecological variables at each occurrence location in order to produce the models. The remaining presences are then retained as test points used in verifying the model’s predictive accuracy (measured as AUC;
Phillips et al. 2006). Considering the small number of settlements in my sample (< 88 in each case), I selected a cross-validation method for the training and test procedure of the models. Cross-validation operates by producing a series of models that retains each individual presence point in turn for testing the model’s predictive accuracy (AUC) while utilizing the remainder of the presence points for training the model (k -1 replicates).
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According to Phillips et al. (2006), it is advisable to run 500 iterations per replicate run.
The end result of the procedure combines the outputs from each replicate run to produce cumulative outputs (i.e. maximum, minimum, average, and lowerci) of the cross-validation procedure along with their associated area under the curve (AUC) evaluation metric.
Evaluating model performance based solely from the AUC values provided by Maxent, however, may be misleading as a number of additional factors also come into play and affect the overall results of the model. Therefore, it is also prudent to consult some additional model evaluation metrics not facilitated directly by the Maxent interface.
4.4.3 Evaluating Maxent model performance: ENMeval
Muscarella et al. (2014) addressed the issue of evaluating Maxent model performance with the development of ENMeval—a statistics package for R Studio (R Core Team 2015).
Maxent by default utilizes five different feature classes (linear, quadratic, product, hinge, and threshold; Table 5) at a regularization multiplier of 1 in producing the models, while other such combinations are possible and may in fact provide more statistically reliable and less overfitted results (Muscarella et al. 2014). The ENMevaluation function included in the ENMeval package is used to run the Maxent algorithm over different sets of modeling parameters, each time adjusting the number of feature classes and the regularization multiplier until every possible combination has been tested along the user defined range of values. Like Maxent, ENMeval allows for user defined settings to be selected in order to fit the desired conditions of the modeling process. For instance, the number of background points sampled by ENMeval can be reduced and the jackknife data partitioning method,
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which is conceptually similar to the cross-validation method used by Maxent—in that it leaves out one occurrence point (k - 1 replicates) in turn for testing the model, can be utilized due to the small overall sample size of archaeological settlements. As such, the
ENMeval procedure can be tuned to best reflect the previously identified desired conditions of the Maxent modeling algorithm.
Table 5: Maxent Feature class types; after Phillips et al. 2006; 2008.
ENMeval generates five evaluation metrics complimentary to the Maxent algorithm to be used in evaluating model performance (Muscarella et al. 2014). Mean AUC
(Mean.AUC) is returned for each of the models and essentially serves the same evaluation function as the AUC provided by Maxent only that ENMeval returns the AUC values of each model adjusted to the different combinations of feature classes and regularization multipliers. Effectively, the latter allows the user to quantify the effects resulting from different combinations of the modeling parameters on the provided AUC measurements. A
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high mean AUC indicates good model performance in discriminating between the presence and pseudo-absence localities of archaeological settlements and thus indicates a strong result. Next, in order to assess model goodness of fit, the mean difference between AUC
(Mean.AUC.DIFF), with regards to the AUC measurements returned on both the testing and training localities respectively, is also provided as an average over each k-bin iteration.
If the mean difference in AUC between training and testing localities is high, it indicates that the parameters have overfit the models to the training localities and that they generally do not perform well in accounting for the occurrence of test localities. A low
Mean.AUC.DIFF is therefore the desired result. Additionally, two metrics on the omission rates of testing localities are also calculated. The first considers the omission rates on test localities as compared with the lowest output value of the training localities
(Mean.ORmin), while the second considers test locality omission rates in comparison with the output values of training localities in exclusion of their lowest ten percent
(Mean.OR10). Those models having the lowest mean omission rates with regards to the testing localities generally perform better in predicting the locations of test occurrences.
Lastly, ENMeval also returns the delta Aikake information criteria adjusted for small sample size (delta.AICc) to assess model complexity. The model having the lowest delta
AICc essentially is identified as providing the best modeled result with the least complex set of modeling parameters. However, because the current work will utilize the logistic output from Maxent and that ENMeval calculates AICc from raw Maxent outputs, I decided not to use the AICc evaluation criteria as the values returned can be different in both the logistic and raw output formats.
By assessing the results of the ENMevaluation process, the optimum combination of
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modeling parameters may be selected for use in running the Maxent algorithm. By order of importance, the model having the lowest Mean.AUC.DIFF, Mean.ORmin, and
Mean.OR10, followed by the highest Mean.AUC, is identified as the most reliable combination of parameters providing the best overall result with the least amount of modeling complexity. However, considering that the goal is to produce comparable models, it should also be noted that the use of different feature classes will affect the potential for inter-model comparisons and therefore whenever possible a similar set of feature classes should be utilized in the production of each model. The optimum types of feature classes— while keeping the former consideration in mind—and the suggested regularization multiplier identified by the ENMevaluation function may then be selected for use in running the Maxent algorithm. Subsequently, the resulting outputs of the Maxent procedure may be compared and interpreted with one another.
4.5 Interpreting the results
4.5.1 Statistics for interpretation: Maxent and ENMTools
The output of the Maxent procedure produces final cumulative models (maximum, minimum, average, and lowerci) compiled from the outputs of each replicate run. In my study I focused on the lowerci models for additional interpretation. The output of the procedure predicts habitat suitability values (ranging from 0% to 100%) onto the study region, effectively identifying the extent of what may be interpreted as the eco-cultural niche of the archaeological population in question. A visual inspection of the mapped distribution of habitat suitability may immediately lead to some qualitative comparisons
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both within and between models with regards to the visual depiction of their geographic distributions. Furthermore, the relative contribution and permutation importance of each ecological variable used in producing the cumulative model is provided by Maxent, effectively highlighting the relative role of the ecological variables used in determining the eco-cultural niche. The value ranges of each ecological variable are also given as response curves representing their individual values—as though it were the only variable considered—and their constrained values—showing the modified value range when taking the effects and relative influence of the additional variables into consideration.
With regards to quantitative interpretation, the relative contribution and permutation importance of each of the ecological variables used in the production of the final models may be assessed and compared with one another. Additionally, by inspecting the response curves for each of the ecological variables the ecological value ranges within which settlements are most likely to be found may be investigated and differentiated. Furthermore, inter-model comparisons on the relative contribution, permutation importance, and response curves of the ecological variables allows for the quantitative characterization of important changes that occur between models produced for each individual period.
Moreover, other comparative metrics that can be used in the interpretation of eco-cultural niche models that are not facilitated by the Maxent procedure directly include calculations of niche overlap and niche breadth. However, such measures can be obtained indirectly from the Maxent outputs through the use of ENMTools.
ENMTools, developed by Warren et al. (2008), works in conjunction with Maxent outputs and can be used to provide additional statistics for the interpretation of diachronic
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differences between the resulting eco-cultural niche models. Niche overlap—a measure on the degree of geographic similarity between the eco-cultural niche predictions—may be calculated within ENMTools from three separate statistics including Schoener’s D
(Schoener 1968), the I statistic (Warren et al. 2008) derived from Hellinger distance (see van der Vaart 1998), and relative rank (RR; Warren and Seifert 2011), each provided along a 0-1 scale in which measures of 0 indicate no niche overlap whereas a measure of 1 indicates perfect niche overlap. Each of the niche overlap statistics highlights a different aspect of the models. For example, the Schoener’s D statistic assumes that the logistic distribution of the eco-cultural niche model also equates with distributions of population density, such that lower and higher habitat suitability values should equal lower and higher population densities respectively (Warren et al. 2008). The biological assumption carried by the Schoener’s D statistic may however not be entirely appropriate in the absence of evidence with regards to actual population densities, thus the I statistic and relative rank statistics of niche overlap may prove more suitable as they do not carry such inherent biological presuppositions (Warren et al. 2008). The I statistic measures the degree of overlap over the entire model and does not discriminate between different habitat suitability values at different localities while the relative rank measure compares absolute differences in the habitat suitability values at each different locality (Warren and Seifert 2011).
Niche breadth—a measure of restriction regarding the value ranges of the ecological variables that a population utilizes relative to the total ecological breadth of the study- region—is also calculated in ENMTools from two statistics using formulas derived from
Levins (1968). The niche breadth statistic indicates whether the eco-cultural niche of the population in question is highly specialized (i.e. restricted in comparison to the total
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available range of ecological conditions) or generalized (i.e. not restricted in comparison to the total available range of ecological conditions). Comparative niche breadth values then may prove useful in assessing the evolutionary trajectory of the population in question.
That is to say, does the eco-cultural niche become more generalized over time? Does it become more specialized? Or if consistently specialized or generalized, are there any noticeable differences between the resulting ecological restrictions between periods? A comparison between the niche overlap and niche breadth values of the different eco-cultural niche models then may serve to highlight important diachronic tendencies in terms of the evolutionary direction of the population serving to ultimately assess the effects of agricultural niche construction.
4.6 Summary – Data and Methods
The considerations of eco-cultural niche modeling, although numerous, can be tailored to the specific research question in order to identify the relevant modeling conditions. For the current purpose of assessing the impacts of niche construction on the evolution of the eco-cultural niche, these include developing the diachronic framework, defining the archaeological population, and selecting the relevant ecological variables. I implemented a periodization for the Neolithic sites by establishing a degree of similarity within the cultural assemblages found at different archaeological settlements, those settlements divided into periods, and the total set selected for the modeling procedure. The periodization system allows any changes to the eco-cultural niche over time to be identified and interpreted in relationship to cultural changes. I established the relevance and availability of ecological
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variables by selecting terrain and bioclimatic conditions that affect the primary subsistence practice of the archaeological population; namely, those variables most closely associated with agricultural production and filtered based on their resolution and ease of availability.
Subsequently, after a review of approaches, I selected a suitable niche modeling algorithm in Maxent, which utilizes a presence-only method based on the locations of the selected archaeological settlements in order to project habitat suitability values across environmental space. Essentially, the spatial distribution of suitability as generated by the
Maxent modeling procedure may be interpreted as the eco-cultural niche of the archaeological population in question. In order to assess model performance, the ENMeval package generates evaluation metrics related to the different possible combination of parameters used in the Maxent algorithm. The combination of modeling parameters that best accounts for the presence of test locations with the lowest amount of modeling complexity is identified by the ENMevaluation function of ENMeval and is selected for the
Maxent procedure. The resulting outputs of the Maxent procedure may then be interpreted in comparison with one another to determine the degree of diachronic change to the eco- cultural niche. The graphic representations can be overlaid to assess qualitative difference while the relative contribution, permutation importance, and response curves provided for the value ranges of the ecological variables can be compared for quantitative differences.
Additionally, statistics of niche overlap and niche breadth calculated via the use of the
ENMTools package can provide other useful quantitative measures to determine the degree of diachronic change.
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Chapter 5 – Application and Results Eco-cultural niche models and metrics for interpretation
5.1 Implementing the methodological approach
The production of eco-cultural niche models and the metrics for their interpretation and evaluation, as outlined in the previous chapter, requires a number of methodological procedures. This chapter presents each in detail. First, Pearson’s test for statistical collinearity is described. Second, the application and results of the ENMevaluation procedure are given. Third, the results from the Maxent eco-cultural niche modeling algorithm are presented. And fourth, the measurements of niche overlap and niche breadth calculated by the ENMTools application are listed. The methodological steps in combination with one another provide the necessary information used in the production of the final eco-cultural niche models and in generating metrics for their subsequent diachronic evaluation.
5.2 Assessing statistical collinearity between independent variables—Pearson’s test
Collinearity describes instances when there is a measurable linear relationship between two variables, which indicates that the two are not wholly independent of each other.
Establishing the degree of collinearity between variable pairs is an important first step in modeling to ensure independence between the predictor variables. In this study, collinearity between potential predictor variables was evaluated using the R package for statistics (R
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Core Team 2015). First, 10,000 location points were randomly sampled from within the boundaries of the study region. The coincident values of the independent variables were then extracted and appended to all 10,000 locations. The latter 10,000 point dataset served as the basis for calculating the Pearson product-moment correlation coefficient (R2) in order to determine the degree of statistical collinearity between the independent variables. The coincident values of the independent variables at each location were paired, their scatterplots/histograms examined, and R2 measured along with their associated p-values
(Fig. 7). Soil typological unit is the only independent variable excluded from Pearson’s test for statistical collinearity as soil types are represented as categorical data and by definition then cannot be collinear in Euclidean space.
Figure 7: Pearson’s test for statistical collinearity (red borders = R2 > 0.8).
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Significant instances of statistical collinearity (R2 > 0.8) were identified between several of the independent variables while two of the independent variables presented no significant instances of collinearity at all—precipitation seasonality and topographic wetness index. Elevation above sea level was found to be collinear with annual precipitation, terrain ruggedness index, mean annual temperature, temperature seasonality, and temperature annual range. Furthermore, annual precipitation is also collinear with mean annual temperature, temperature seasonality, and temperature annual range; the terrain ruggedness index is collinear with slope and annual mean temperature; and temperature seasonality with mean annual temperature and temperature annual range. Those variables presenting significant instances of collinearity were then excluded from further analyses.
Namely, elevation above sea level, annual precipitation, terrain ruggedness index, and temperature seasonality were each removed. Six independent variables remain— precipitation seasonality, slope, annual mean temperature, temperature annual range, topographic wetness index, and soil typological unit, the latter of which was exempt from
Pearson’s test.
Table 6: Independent ecological variables retained after Pearson's test.
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The six remaining independent variables in conjunction with one another provide an adequate coverage of the overall ecological conditions of the Struma River Valley (Tables
6 & 7). Slope, topographic wetness index, and soil typological unit collectively provide relevant information on the characteristics of the terrain while in isolation also convey meaningful details not accounted for by the other variables. Mean annual temperature, temperature annual range, and precipitation seasonality together cover climatic variability within the study region and precipitation seasonality also accounts for important differences in the hydrological cycle.
Table 7: Soil types and surface area (ESDAC).
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5.3 Producing the eco-cultural niche models—ENMeval and Maxent
For the purpose of evaluating diachronic change to the eco-cultural niche, I decided to produce three general models and two subset models with regards to the Neolithic Period in the Struma River Valley. One eco-cultural niche model each is produced from the Early
Neolithic (33 presences), Middle Neolithic (42 presences), and Late Neolithic (88 presences) datasets. Furthermore, considering the evidence of strong cultural diversification during the Late Neolithic Period, two subset models are additionally produced in this regard. The two subset models are produced more strictly by subdividing the Late Neolithic dataset to account for the distribution of Vinča B cultural elements (31 presences) and the distribution of the joint Topolnitsa/Akropotamos cultural grouping (23 presences; see Table 3). Those Late Neolithic settlements pertaining to neither the Vinča B nor the Topolnitsa/Akropotamos groups, or otherwise presenting unclear evidence, were used only in the production of the general Late Neolithic eco-cultural niche model.
Although there is evidence for cultural diversification also in both the Early and Middle
Neolithic Periods, first the degree of diversification appears minimal by comparison with that of the Late Neolithic Period, and second their limited sample size precludes any benefits that may be derived from subdividing the respective datasets.
5.3.1 Selecting the modeling parameters—ENMeval
In order to select the optimum combination of feature classes and the most appropriate regularization multiplier for use in running the Maxent algorithm, all models were first evaluated using the ENMeval package for R (Muscarella et al. 2014). The presence datasets
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were each partitioned using the jackknife (k - 1) method with one presence location retained per replicate run as a test with the total number of replicates equal with the total number of presences. The latter produces cumulative replicate outputs, with each presence point in turn having been retained as a test locality. Thirty-six separate models representing all possible feature class combinations at regularization multipliers ranging between 0.5 and 3
(at 0.5 intervals) were generated by the ENMeval application from each of the presences datasets. Of the thirty-six models produced per dataset, the model having the lowest mean area under the curve difference (Mean.AUC.DIFF), mean minimum training presence omission rate (Mean.ORmin), and mean ten percent training presence omission rate
(Mean.OR10), followed by the highest mean area under the curve (Mean.AUC) is identified as the most reliable combination of parameters providing the best overall result with the least amount of modeling complexity (see Section 4.4.3). Four out of the five final models could be selected by maintaining a strict adherence with the abovementioned criteria; however, in one case (the Topolnitsa/Akropotamos subset model) it was necessary to invert the importance of Mean.OR10 and Mean.AUC so that a comparable feature class combination could be selected for the production of all final models. The choice of feature class combinations affects the overall shape of the independent variable response curves produced by Maxent and as such can limit the potential for inter-model comparisons (see
Table 5). Therefore, when merited, I selected a similar feature class combination for the production of all final models.
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Early Neolithic: ENMevaluation
In accordance with the abovementioned criteria, the optimal modeling parameters identified by ENMeval for the Early Neolithic dataset (see Section 4.2) consist of the linear, quadratic, hinge, and product feature class combination at a regularization multiplier of 2.5
(referred to as ‘LQHP-2.5’). The average difference in AUC between training and testing datasets (Mean.AUC.DIFF) is 3%, indicating that the modeling parameters consistently perform well in accounting for the occurrence of test localities. The mean minimum training presence omission rate (Mean.ORmin) is 3%, and the mean ten percent training omission rate (Mean.OR10) is 12%. Considering that the total number of test localities is equal to the total number of presences, the omission rates (Mean.ORmin and Mean.OR10, respectively) indicate that an average of one test location and four test locations out of thirty-three total were omitted, which is within reasonable difference of the expected 0% and 10% omission rate thresholds. The returned mean AUC (Mean.AUC) is 94% (Fig. 8).
Figure 8: Early Neolithic ENMevaluation results (optimum parameters indicated with star).
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Middle Neolithic: ENMevaluation
The optimal modeling parameters identified by ENMeval for the Middle Neolithic dataset
(see Section 4.2) consist of the linear, quadratic, and hinge feature class combination at a regularization multiplier of 1 (LQH-1). The average mean difference in AUC between training and testing datasets (Mean.AUC.DIFF) is 6%, indicating that the model consistently performs well in accounting for the occurrence of test localities. The mean minimum training presence omission rate (Mean.ORmin) is 2%, and the mean ten percent training omission rate (Meanr.OR10) is 12%. The omission rates (Mean.ORmin and
Mean.OR10, respectively) indicate that an average of 0.84 and five test locations out of forty-two were omitted, within reasonable difference of the expected 0% and 10% omission rate thresholds. The mean AUC (Mean.AUC) returned is 89% (Fig. 9).
Figure 9: Middle Neolithic ENMevaluation results (optimum parameters indicated with star).
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Late Neolithic: ENMevaluation
The optimal modeling parameters identified by ENMeval for the Late Neolithic dataset (see
Section 4.2) consist of the linear, quadratic, and hinge feature class combination at a regularization multiplier of 2.5 (LQH-2.5). The Mean.AUC.DIFF is 6%, Mean.ORmin is returned at 1%, and Mean.OR10 is 10%. The omission rates indicate that an average of
0.88 and 8.8 test localities out of eighty-eight were omitted respectively, within reasonable difference of the expected 0% and 10% testing omission rate thresholds indicating very little to no model overfit. Mean.AUC equals 87% (Fig. 10).
Figure 10: Late Neolithic ENMevaluation results (optimum parameters indicated with star).
Vinča B—Late Neolithic subset: ENMevaluation
The optimal modeling parameters identified by ENMeval for the Vinča B—Late Neolithic subset (see Section 4.2) model consist of the linear, quadratic, and hinge feature class
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combination at a regularization multiplier of 1 (LQH-1). The Mean.AUC.DIFF is 7%, the
Mean.ORmin returned is 3%, and Mean.OR10 is 13%. One and four out of the thirty-one test localities were on average omitted, as indicated by the Mean.ORmin and MeanOR10 measurements respectively, suggesting little to no model overfit. Mean.AUC is measured at 89% (Fig. 11).
Figure 11: Vinča B ENMevaluation results (optimum parameters indicated with star).
Topolnitsa/Akropotamos—Late Neolithic subset: ENMevaluation
As previously mentioned, in order to produce comparable independent variable response curves, in the interest of facilitating inter-model evaluations, a similar set of feature class combinations should be selected in the production of each final eco-cultural niche model.
Considering that the ENMeval procedure for each of the previous models identified linear, quadratic, and hinge feature class combinations (with the added inclusion of product in the
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Early Neolithic model) as the optimum set of modeling parameters, I decided to select the fourth best (LQH-3) out of the thirty-six models produced by ENMeval for the
Topolnitsa/Akropotamos—Late Neolithic dataset (see Section 4.2). The top three models only utilized linear and/or quadratic feature classes in the absence of hinge, which produces significantly different variable response curve shapes. Thus, the optimum modeling parameters selected for the Topolnitsa/Akropotamos subset model consist of the linear, quadratic, and hinge feature class combination at a regularization multiplier of 3 (LQH-3).
The Mean.AUC.DIFF is 4%, Mean.ORmin is 4%, and Mean.OR10 is 22%. The respective omission rates identify that an average of one test locality and five test localities were omitted out of twenty-three total, indicating little to no model overfit in the first case and moderate model overfit in the second case. Mean.AUC is measured at 92% (Fig. 12).
Figure 12: Topolnitsa/Akropotamos ENMevaluation results (optimum parameters indicated with star).
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5.3.2 Running the modeling algorithm—Maxent
The final eco-cultural niche models were produced in Maxent using the optimum combination of modeling parameters identified by the ENMeval procedure. One model each was produced from the Early Neolithic, Middle Neolithic, Late Neolithic, Vinča B, and Topolnitsa/Akropotamos datasets using the cross-validation data partitioning method, which retains one presence point per replicate run for testing the model with the total number of replicates equal to the total number of presences. 500 iterations were produced per replicate run. The final models consist of combining the cumulative outputs of the cross-validation procedure, in turn producing maximum, minimum, average, and lowerci habitat suitability grids. Specifically, I selected the lower confidence interval models (at
95%) for additional interpretation (Fig. 13)
5.4 Generating metrics for interpretation—Maxent and ENMTools
Aside from the production of the eco-cultural niche models themselves, Maxent also generates metrics for interpretation in the form of independent variable response curves and lists the independent variables’ percent contribution and permutation importance. With regards to the independent variable response curves, only those indicating the dependency of predicted habitat suitability values are here presented. Alternatively, the response curves used to demonstrate the marginal effects of modifying the value of only one variable at a time while keeping all others at their average sample value, though useful in determining the effects of the independent variable on the production of the overall model, are less useful in terms of characterizing the dependencies of the eco-cultural niche. Therefore, I
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Figure 13: Maxent eco-cultural niche models.
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decided to focus my investigation on the former response curves rather than on the latter.
Concerning the independent variables’ percent contributions, percent contribution values depend entirely on the path taken by the Maxent algorithm in producing the final model and should be interpreted with caution in light of independent variable collinearity.
Permutation importance on the other hand depends only on the final model and indicates how strongly the habitat suitability values depend on particular independent variables and expressed as percentages. Permutation importance is then more informative than percent contribution in characterizing the eco-cultural niche dependencies on the independent variables. Furthermore, the ENMTools application (Warren 2008) is utilized to calculate three niche overlap statistics (Schoener’s D, the I statistic, and Relative Rank) and two niche breadth metrics (B1 and B2; Levins 1968) from the Maxent lowerci outputs.
5.4.1 Maxent model results and metrics for interpretation
The Early Neolithic eco-cultural niche model
The percent contribution and permutation importance of the original six independent variables (i.e., Tables 6 & 7 from pgs 79 & 80) used in producing the Early Neolithic eco- cultural niche model are presented in Table 8. The path taken by the Maxent algorithm indicates that soils, topographic wetness index, and temperature annual range contributed significantly in the production of the model at 35.9%, 30.4%, and 19.4% respectively. The other independent variables (namely, annual mean temperature, slope, and precipitation seasonality) contributed less than 10% each. Permutation importance, on the other hand, is more indicative of the actual dependencies between the location of archaeological
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settlements and the ecological conditions of the study region and is therefore more informative. The permutation importance of the independent variables in descending order are temperature annual range (30.5%), precipitation seasonality (27.6%), topographic wetness index (22.5%), soil typological unit (15.4%), slope (2.3%), and annual mean temperature (1.7%).
An examination of the independent variable response curves indicates the dependencies of the Early Neolithic habitat suitability values on the ecological conditions of the study region (Fig. 14). The habitat suitability dependencies are here presented by order of decreasing permutation importance. Habitat suitability values are positively correlated with an increasing annual temperature range with over 70% habitat suitability having been attributed to a 33 °C annual temperature range and decreasing sharply to 0% probability from 31 to 25 °C. Habitat suitability (~60%) is greatest in areas with 20% precipitation seasonality decreasing sharply to 10% probability below that threshold and decreasing more smoothly until reaching 0% probability in areas having a precipitation seasonality of
45%. A greater than 60% habitat suitability value is uniformly attributed to areas with a moderate to high topographic wetness index (between 8 and 20) and decreases sharply to
0% probability in areas below 8. Dependencies on the soil typological unit designate a greater than 70% probability for vertic-chromic luvisols, followed by a 67% probability on fluvi-calcaric fluvisols, and 45% probability on pellic vertisols. Dependencies on all other soil types are less than 22%. Greater than 60% habitat suitability is indicated in areas having a 0° slope and is negatively correlated with increasing terrain inclination until reaching 0% probability at 25° or more. A 70% habitat suitability value is associated with a mean annual temperature of 12 °C, smoothly decreasing towards lower mean annual temperatures and
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Table 8: Early Neolithic independent variable percent contribution and permutation importance.
Figure 14: Early Neolithic independent variable response curves.
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decreases to a 20% probability plateau at 15 °C or greater.
The Middle Neolithic eco-cultural niche model
The percent contribution and permutation importance of the independent variables used in producing the Middle Neolithic eco-cultural niche model are presented in Table 9. The path taken by the Maxent algorithm indicates that soils, mean annual temperature, and topographic wetness index contributed significantly in the production of the model at
43.2%, 35%, and 16% respectively. The other independent variables (namely slope, temperature annual range, and precipitation seasonality) contributed less than 10% each.
The permutation importance of the independent variables in descending order are mean annual temperature (58.1%), soil typological unit (15.2%), precipitation seasonality
(11.5%), topographic wetness index (8.7%), temperature annual range (6.4%), and slope
(0.1%).
An examination of the independent variable response curves indicates the dependencies of the Middle Neolithic habitat suitability values on the ecological conditions of the study region (Fig. 15). Habitat suitability dependencies are presented by order of decreasing independent variable permutation importance. A 65% habitat suitability value is associated with a mean annual temperature of ~15 °C, decreasing smoothly to 45% probability until reaching 11 °C and decreasing sharply to 0% at 4 °C. A sharp decrease is noted in mean annual temperatures greater than 15 °C until reaching a 25% probability plateau at post 16
°C. Dependencies on the soil typological unit designate a 70% probability for vertic- chromic luvisols, followed by a 62% probability on calcaro-vertic cambisols, and between
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Table 9: Middle Neolithic independent variable percent contribution and permutation importance.
Figure 15: Middle Neolithic independent variable response curves.
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45% to 50% probability on fluvi-calcaric fluvisols, calcaric regosols, and calcaric fluvisols.
Dependencies on all other soil types are less than 12%. Habitat suitability (~72%) is greatest in areas with 45% precipitation seasonality, decreasing smoothly to a 45% probability plateau between 25 and 27% seasonality, increasing again to 52% probability at 19% seasonality, and finally decreases sharply to 0% probability at 16% seasonality. A greater than 60% habitat suitability value is uniformly attributed to areas with a moderate to high topographic wetness index (between 7 and 20) and decreases sharply in areas below a wetness index value of seven. Habitat suitability values are positively correlated with increasing annual temperature range with over 65% habitat suitability having been attributed to a 31 °C annual temperature range, while decreasing to a 50% probability plateau at a 33 °C range. Greater than 60% habitat suitability is indicated in areas having a
0° slope and is negatively correlated with increasing terrain inclination until reaching 0% at 30°, however the general probability for settlement is greater between 0° and 30° than for the Early Neolithic model.
The Late Neolithic eco-cultural niche model
The percent contribution and permutation importance of the independent variables used in producing the Late Neolithic eco-cultural niche model are presented in Table 10. The path taken by Maxent indicates that annual mean temperature, topographic wetness index, soils, and slope contributed significantly in the production of the model at 38.5%, 25.3%, 22.9%, and 12.7% respectively. The other independent variables (namely, precipitation seasonality and temperature annual range) contributed less than 1% each. The permutation importance
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of the independent variables in descending order are annual mean temperature (47.7%), soil typological unit (27.8%), topographic wetness index (13.8%), slope (9.4%), precipitation seasonality (0.9%), and temperature annual range (0.4%).
An examination of the independent variable response curves indicates the dependencies of the Late Neolithic habitat suitability values on the ecological conditions of the study region (Fig. 16). Habitat suitability dependencies are presented by order of decreasing permutation importance. Habitat suitability values are positively associated with increasing mean annual temperature reaching a 70% probability at 15 °C until decreasing to 60% probability at 16 °C or more. Dependencies on the soil typological unit designate a 75% probability for calcaro-vertic cambisols, a 62% probability on calcaric regosols, 60% probability on calcaric fluvisols, 58% on vertic-chromic luvisols, 52% on fluvi-calcaric fluvisols, and between 38-42% probability on all other soil types with the exception of calcaric lithosols and dystric cambisols at 12% probability or less. A greater than 65% habitat suitability value is attributed to areas with a very high topographic wetness index
(between 18 and 20), decreasing to 60% until reaching a value of 8, and sharply decreases between 8 and 5 to 0% probability. Greater than 65% habitat suitability is indicated in areas having a 0° slope and is negatively correlated with increasing terrain inclination until reaching 0% at 26°. Habitat suitability (70-72%) is greatest in areas with 35% precipitation seasonality or more, decreasing smoothly to 38% probability at 20% precipitation seasonality, and decreases sharply to 0% probability at 15%. Habitat suitability values are positively correlated with increasing annual temperature range with over 75% habitat suitability having been attributed to a range of 33 °C.
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Table 10: Late Neolithic independent variable percent contribution and permutation importance.
Figure 16: Late Neolithic independent variable response curves.
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Vinča B-Late Neolithic subset eco-cultural niche model
The percent contribution and permutation importance of the independent variables used in producing the Vinča B-Late Neolithic subset eco-cultural niche model are presented in
Table 11. The path taken by the Maxent algorithm indicates that soils, temperature annual range, topographic wetness index, and precipitation seasonality contributed significantly in the production of the model at 37.1%, 25.7%, 22.6%, and 10.9% respectively. The other independent variables (namely, annual mean temperature and slope) contributed less than
3% each. The permutation importance of the independent variables in descending order are temperature annual range (40.6%), precipitation seasonality (38.7%), topographic wetness index (12.2%), soil typological unit (8.1%), slope (0.3%), and annual mean temperature
(0.1%).
An examination of the independent variable response curves indicates the dependencies of the Vinča B-Late Neolithic habitat suitability values on the ecological conditions of the study region (Fig. 17) and presented here by order of decreasing permutation importance.
Habitat suitability values are positively correlated with and increasing annual temperature range with over 70% habitat suitability having been attributed to a 33 °C range and decreasing sharply from a range of 32 to 27 °C until reaching 0% probability. Habitat suitability (~60%) is greatest in areas with 21% precipitation seasonality decreasing sharply to 15% probability at 15% seasonality and to 0% probability at 35% seasonality. A 65% habitat suitability value is attributed to areas with a moderate topographic wetness index
(between 8 and 10) decreasing smoothly to 50% in areas with a high topographic wetness index (between 10 and 20), while the probability for settlement decreases sharply to 0%
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Table 11: Vinča B independent variable percent contribution and permutation importance.
Figure 17: Vinča B independent variable response curves.
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from a twi value of 8 to 6. Dependencies on the soil typological unit designate a 72% probability on fluvi-calcaric fluvisols, followed by a 62% probability for vertic-chromic luvisols, 55% on pellic vertisols, 25% on calcaric fluvisols, 22% on chromic luvisols, and
15% on all other soil types. More than 70% habitat suitability is indicated in areas having a 4° slope, decreasing sharply to 35% probability on flat (0°) terrains, and is negatively correlated with increasing terrain inclination until reaching 0% probability at 35°. A 70% habitat suitability value is associated with a mean annual temperature of 12 °C, smoothly decreasing towards lower mean annual temperatures and decreases to a 22% probability plateau at 15 °C or greater.
Topolnitsa/Akropotamos-Late Neolithic subset eco-cultural niche model
The percent contribution and permutation importance of the independent variables used in producing the Topolnitsa/Akropotamos-Late Neolithic subset eco-cultural niche model are presented in Table 12. The path taken by the Maxent algorithm indicates that only mean annual temperature contributed significantly in the production of the model at 89.1% while all other independent variables contributed less than 7% each. The same circumstance is repeated for permutation importance in that mean annual temperature accounts for 93% of the model with slope at 6.8%, soil typological unit at 0.2%, and precipitation seasonality, topographic wetness index, and temperature annual range each at 0%.
An examination of the independent variable response curves indicates the dependencies of the Topolnitsa/Akropotamos-Late Neolithic subset habitat suitability values on the ecological conditions of the study region (Fig. 18) and is here presented by order of
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Table 12: Topolnitsa/Akropotamos independent variable percent contribution and permutation importance.
Figure 18: Topolnitsa/Akropotamos independent variable response curves.
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decreasing permutation importance as listed above. A 70% habitat suitability value is associated with a mean annual temperature of ~15 °C, decreasing sharply to 0% probability until reaching 8 °C and to a 42% probability plateau at 16 °C. Greater than 60% habitat suitability is indicated in areas having a 0° slope and is negatively correlated with increasing terrain inclination until reaching 0% at 22°.
Dependencies on the soil typological unit designate an 85% probability on calcaro-vertic cambisols, followed by a 70% probability on calcaric fluvisols, 55% on calcaric regosols,
37% on vertic-chromic luvisols, 30% on chromic luvisols, and 25% on all other soil types.
Habitat suitability is positively correlated with increasing precipitation seasonality with
80% probability associated with an excess of 45% precipitation seasonality. A greater than
60% habitat suitability value is near uniformly attributed to areas with a moderate to high topographic wetness index (between 8 and 20) and decreases sharply to 0% probability in areas with a twi value below 8. Habitat suitability values are positively correlated with increasing annual temperature range with over 65% habitat suitability having been attributed to a 33 °C range.
5.4.2 Eco-cultural niche overlap and breadth statistics—ENMTools
The lowerci (95% confidence interval) habitat suitability grids produced by the Maxent algorithm were selected for use in the calculation of niche overlap and niche breadth statistics using ENMTools (Warren 2008). The parameters of ENMTools were modified to account for the logistic habitat suitability values of the lowerci output grids and a small grid filter pass was selected for the calculation of the niche overlap and niche breadth statistics,
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which also allowed ENMTools to measure the relative rank niche overlap metric. The Early
Neolithic, Middle Neolithic, Late Neolithic, Vinča B subset, and Topolnitsa/Akropotamos subset lowerci grids were all paired in order to calculate the Schoener’s D (Table 13), I statistic (Table 14), and relative rank (RR; Table 15) niche overlap metrics. The B1 and B2 niche breadth statistics based on Levins (1968) were also calculated from every lowerci output grid and are presented in Table 16.
Table 13: Schoener’s D niche overlap statistic (0 = no overlap, 1 = perfect overlap).
Table 14: the I method niche overlap statistic (0 = no overlap, 1 = perfect overlap).
Table 15: Relative rank niche overlap statistic (0 = no overlap, 1 = perfect overlap).
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Table 16: Niche breadth statistic; after Levins 1968.
5.5 Application and results—summary
I applied Pearson’s test to identify significant instances of statistical collinearity (R2 > 0.8) between the independent ecological variables. Following Pearson’s test, four out of ten independent variables presented several instances of collinearity and were removed from further analyses (elevation above sea level, terrain ruggedness index, annual precipitation, and temperature seasonality) leaving terrain slope, soil typological unit, topographic wetness index, precipitation seasonality, mean annual temperature, and temperature annual range for the final production of the eco-cultural niche models. I then utilized the
ENMevaluation procedure to determine the optimum combination of modeling parameters providing the best overall result with the least amount of modeling complexity for each of the presences datasets to be used in running the Maxent algorithm. The Maxent algorithm was run in accordance with the results of the ENMeval procedure to produce eco-cultural niche models for the Early Neolithic, Middle Neolithic, Late Neolithic, Vinča B, and
Topolnitsa/Akropotamos datasets. Furthermore, the Maxent procedure generated metrics for interpretation, such as the independent variable percent contribution and permutation importance—serving to describe the effects of each independent variable on the production of the model—as well as the independent variable response curves that I then utilized to elaborate on the dependency of the eco-cultural niche based on the variability of the
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ecological conditions in the study region. Lastly, I calculated niche overlap and niche breadth statistics from the ENMTools application for each of the eco-cultural niche models.
In the next chapter, I use these findings to discuss the broader context of the Early to Late
Neolithic niche selection, settlement patterns, and cultural evolution in the Struma River
Valley.
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Chapter 6 – Interpretation Eco-cultural niche evolution during the Neolithic of the Struma River Valley
6.1 Defining the eco-cultural niche
I presented the results of the Early, Middle, and Late Neolithic (and Late Neolithic subset) eco-cultural niche models in Chapter 5. I subsequently projected habitat suitability values
(ranging from 0 to 100%) across the study region (see Figure 13) effectively delineating the extent of what may be interpreted as the preferred eco-cultural niche of the archaeological populations in question. However, habitat suitability values are themselves dependent on co-occurring instances of particular ecological conditions. That is to say, the eco-cultural niche is defined by particular dependencies driven by an interacting set of semi-independent ecological variables within which archaeological settlements are found.
These dependencies should then be taken into account when interpreting the final results and each independent ecological variable taken as an important component of the total system. Furthermore, it is critical to recognize that while some co-occurring sets of ecological conditions present a greater probability for settlement based on the latter dependencies, a low probability for settlement is still potentially suitable for habitation and should nonetheless be considered as an integral component of the eco-cultural niche.
Therefore, the eco-cultural niche is here defined as the total set of ecological conditions— locations with a probability of greater than zero—within which settlements from a particular archaeological population may be found.
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6.1.1 Issues of interpretation
The interpretation of the eco-cultural niche in consideration of the relationship between culture and ecology, on the other hand, is a different matter. It should be recalled that I defined the archaeological populations in question based on similarities between their cultural repertoires and in their chronological affiliation across sites (see Section 4.2).
However, it is probable that some cultural traits are more likely to be directly affected by ecological conditions. For instance, while subsistence practices are often directly restricted by environmental conditions, it is more difficult to argue that decorative pottery types are equally as restricted by ecology. I argued in Chapter 2 that adaptation to an eco-cultural niche is likely to have consequences across the biological, cultural, and ecological inheritance systems (Odling-Smee et. al 2003). Thus, considering that the eco-cultural niche is defined by the ecological distribution of culturally adaptive systems, correlations drawn between cultural evolutionary pathways and shifts in the ecological setting can also be advanced.
In this chapter, I will characterize and interpret the eco-cultural niche of the Early,
Middle, and Late Neolithic (and Late Neolithic subset) populations of the Struma River
Valley in light of the cultural evolutionary process. Based on the evidence for cultural diversification both within and between periods, I will demonstrate how culture has produced, responded, or remained indifferent to shifts in the eco-cultural niche.
Furthermore, diachronic considerations derived from niche overlap and niche breadth statistics will be used to elaborate on the greater outcomes and evolutionary consequences of such shifts in the relationship between culture and ecology.
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6.2 The Early Neolithic eco-cultural niche
The results of the eco-cultural niche modeling procedure for the Early Neolithic have effectively identified the subset of ecological conditions within which settlements of this period are found. With regards to the physical characteristics of the Struma River Valley, there is a clear preference for flatter terrains (0° slope), a high topographic wetness index
(between 8 and 20), and for settlement on soils of the fluvisol and luvisol types. The bioclimatic variables indicate a dependency on high temperature annual ranges (decreasing from 33 °C), moderate mean annual temperatures (~12 °C), and low precipitation seasonality (decreasing in probability from 20%). The results also indicate a lesser but still considerable probability for settlement on slightly sloped terrains, lower topographic wetness indexes, occasionally in warmer climates, and on soils of the vertisol type.
When taken in unison, this particular subset of ecological characteristics provides meaningful insight into the eco-cultural relationship during the Early Neolithic Period.
Generally, flat terrains with a high topographic wetness index are more suitable for early agricultural practices in that they capture and retain more moisture per land area than do steeper terrains more susceptible to water runoff. The probability for settlement is also highest on soils of the fluvisol and luvisol types, both of which are light and easily worked soils capable of growing a wide range of crops without the use of the plough or irrigation.
All three of these terrain characteristics tend to converge on or very near to the banks of the Struma River and its principal tributaries as well as on the gently sloped forested landscapes near the valley bottoms, suggesting ready access to a water source and the replenishment of nutrients to soils from regular overbank flooding. Furthermore, high
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temperature annual range, moderate mean annual temperature, and low precipitation seasonality indicate the occurrence of frost and a lesser risk of extended drought. These bioclimatic characteristics are generally confined to the Middle and Upper Struma
Valleys—in the sub-Mediterranean and Continental climatic zones—with zero per cent probability for settlement attributed to almost all of the Lower Struma Valley, which is consistent with the lack of Early Neolithic settlement in the sub-region. Finally, the relatively well defined eco-cultural niche, as here identified by the modeling procedure with a narrow range of ecological variability, provides no evidence that different subset
Early Neolithic populations occupied substantially different eco-cultural niches; thus, any differences between them can only be explained by cultural and/or historical contingencies.
Overall, the Early Neolithic eco-cultural niche coincides with a preference for excellent and easily worked agricultural lands in more temperate climates that can be exploited for sowing both winter and summer crops. There is evidence for both winter and summer sowing during the Early Neolithic; emmer wheat—which thrives in ideal growing conditions—is the dominant crop type by the second half of the period; and the importance of legumes has been noted as potentially providing a good source of protein, perhaps mitigating the difficulties associated with establishing adequate herd size during the first developmental stages of the Neolithic in the region (Marinova and Popova 2007).
Agricultural production was thus of the utmost importance and settlements were located accordingly. Wild resources are also more heavily exploited throughout the Early Neolithic
Period (Marinova 2006; Marinova 2009; Marinova and Thiebault 2008; Marinova et al.
2016) and were perhaps similarly utilized in order to mitigate dietary deficiencies.
Settlement along or near rivers and forested hillsides would have, in fact, also provided
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ready access to a number of different ecotones useful for the hunting and gathering of wild resources both for dietary and utilitarian needs (Marinova and Thiebault 2008; Marinova et al. 2016).
The more marginal characteristics of the eco-cultural niche, however, such as settlement on soils of the vertisol type, slightly steeper slopes, lesser topographic wetness indexes, and different climates are also important to consider. Vertisols, for instance, are suitable for grazing, the collection of woodland resources, and growing post-rainy season crops. The marginal settlements are generally located farther to the north and also coincide with the few Early Neolithic settlements at which einkorn wheat dominates over emmer (Marinova
2006). The ecological properties of these marginal settlements then might indicate that they relied more heavily on sheep and goat herding (sheep and goat being the dominant animal domesticate during the Early Neolithic; see Marinova et al. 2016). Alternatively, they may have also utilized a different crop composition in order to mitigate the local ecological conditions. Most importantly, however, the marginal characteristics of the Early Neolithic eco-cultural niche are located just on the fringes of what may be interpreted as the core eco- cultural niche as defined by its high agricultural potential. The latter suggests not only a tendency but also the ability to mitigate local ecological conditions via the reconstruction of the early agricultural niche and expand over the landscape (within reason) despite possible environmental limitations.
6.3 The Middle Neolithic eco-cultural niche
With regards to the physical characteristics of the Struma River Valley, Middle Neolithic
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settlements are preferentially located on flatter terrains (0° slope), but sloped terrains (up to 30°) are now more probable than during the Early Neolithic Period. A moderate to high topographic wetness index (between 7 and 20) is the norm and while soils of the fluvisol and luvisol types still garner high habitat suitability values, soil suitability has also expanded with high probability values accorded to regosols and cambisols as well. The bioclimatic variables indicate a preference for a more moderate temperature annual range
(decreasing in probability from 31 °C), a high mean annual temperature (~15 °C), and considerable variability in preference for precipitation seasonality (with dual high peaks of probability at 45% and 19%, respectively). Generally, the eco-cultural niche of the Middle
Neolithic population has expanded to include more of the ecological variability present in the Struma River Valley.
This particular subset of ecological characteristics provides insight into how the settlement pattern and the agricultural niche evolved between the Early and Middle
Neolithic Periods. Rather than having abandoned the Early Neolithic eco-cultural niche, populations expanded to include more of the surrounding landscape, most notably towards the south. The similarities between the Early Neolithic and Middle Neolithic eco-cultural niches are clearly driven by the continued occupation of the Early Neolithic settlements in the Upper Struma Valley, at which there are no discernible Middle Neolithic horizons despite the presence of black polished ceramics (diagnostic for the Middle Neolithic
Period). The evident differences, however, are driven by the establishment of all new settlements in the Middle Struma Valley at which the black polished Dolna-Ribnitsa pottery type (and variants thereof) has also been identified and in the Lower Struma Valley, which was settled comparatively later at the transition to the Late Neolithic Period.
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First are the settlements that continue from the Early Neolithic tradition in the Upper
Struma Valley and generally conform to the characteristics of the core Early Neolithic eco- cultural niche with its high agricultural potential. Second are the new southern settlements, in the Middle and Lower Struma Valleys, most with no clear indication of previous Early
Neolithic habitation. Although there is limited evidence with regards to subsistence practices during the Middle Neolithic Period, some suggestions have nonetheless been advanced based on the new types of settlements and their locations. The geomorphological characteristics of the newly erected settlements in the Middle Struma Valley, for instance, appear to indicate a preference for hunting and/or stock breeding and not agriculture as they are located in the lower foothills of the Ograzhden and Pirin Mountains comparatively farther away from prime agricultural lands (Perničeva 1983). Additionally, the change in soil type probability, now including cambisols and regosols, is a result of new settlement in the Lower Struma Valley—as are the high probabilities for warmer climates and increased precipitation seasonality—where these soil types are most prominent. Cambisols are good agricultural soils, however much less easily worked than luvisols and fluvisols, and are equally suited for grazing. Regosols, on the other hand, are not suitable for agriculture without irrigation, but are typically used for extensive grazing purposes.
Although limited, information about subsistence practices in the Middle and Lower Struma
Valleys (namely only that available from Sitagroi) supports the claim that stock breeding perhaps increased in importance during the Middle Neolithic Period in that the proportion of cattle represents 34% of the total faunal assemblage as compared with an approximate average of 15% at settlements from the Early Neolithic Period. Additionally, einkorn wheat—which can overtake the yield of emmer in less suitable agricultural conditions
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(Marinova and Popova 2007)—regains importance to make up the dominant crop type of the paleobotanical assemblage.
6.3.1 Niche construction in the Middle Neolithic and divergence of the eco-cultural niche
This characterization of the Middle Neolithic eco-cultural niche then brings to light many considerations with regards to the eco-cultural relationship and the cultural evolutionary process in the Struma River Valley. For one, it is probable that there are actually two and possibly even three distinct core eco-cultural niches co-occurring during the Middle
Neolithic Period here necessarily masked by the use of a single overarching diagnostic ceramic category—namely black polished ware—as a population discriminator. The latter case exemplifies the role of historical and cultural contingencies operating alongside niche construction and eco-cultural niche inheritance in the diversification of cultural traits.
Generally, there is a definite shift in the eco-cultural relationship between the Early and
Middle Neolithic Periods identified with the introduction of black polished pottery as a population discriminator. However, the eco-cultural shift is far more pronounced in the
Middle and Lower Struma Valleys, while in the Upper Struma Valley the eco-cultural niche largely remains the same as during the Early Neolithic Period with the omission of only the most northern settlements at which black polished pottery has also notably not been recorded. It can be argued that black polished pottery is therefore most likely to have arrived in the north as the result of diffusion from the Middle Struma Valley, bearing little to no consequence by way of additional change to the eco-cultural relationship. To the south, however, the development of black polished pottery coincides with a more strongly
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emphasized local expression in the Middle Struma Valley—as is exemplified by the Dolna-
Ribnitsa variant—in association with an equally strong shift in the eco-cultural relationship.
The latter is also potentially associated with an increase in the importance of stock breeding, which would have accommodated settlement on more agriculturally marginal landscapes in the Middle Struma Valley and later into the Lower Struma Valley as well. This divergent shift in the eco-cultural relationship established during the Middle Neolithic Period then may have acted as the catalyst towards even greater episodes of cultural diversification moving next into the Late Neolithic Period.
6.4 The Late Neolithic eco-cultural niche
The results of the eco-cultural niche modeling procedure for the Late Neolithic population has identified a rather wide range of ecological conditions within which settlements of this period may be found. There is, however, a preference for flat terrain (0° slope) and a very high topographic wetness index (between 18 and 20). Dependencies on soil types have expanded to include 38% probability or more on all soil types with the exception of calcaric lithosols and dystric cambisols representing 12% probability or less. The bioclimatic variables are similarly spread out, though they demonstrate a tendency for increased probability in low temperature annual ranges, high mean annual temperatures, and moderate precipitation seasonality. In general, the pattern suggests a high probability for settlement coinciding with prime agricultural lands—on flat terrains and a high topographic wetness index—however the ecological dependencies are sufficiently broadened to include even the most marginal areas of the landscape suggesting either improved agricultural
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practices or a mixed subsistence economy. Essentially, the eco-cultural niche of the Late
Neolithic Period has expanded to include nearly all of the habitable terrain in the Struma
River Valley excluding only the alpine and sub-alpine regions.
The Late Neolithic eco-cultural niche model was produced using all the settlements attributed to this period and/or present evidence of black-topped ceramics, which is diagnostic for the Late Neolithic in the entire Struma River Valley. There is, however, significant cultural variability between settlements as well with the identification of the
Vinča B, Topolnitsa, Akropotamos, Strumsko, and Galepsos populations having been noted, effectively subdividing the Late Neolithic Period into several different potential populations of interest. For these reasons, I consider the Late Neolithic eco-cultural niche model a broad generalization that most certainly masks considerable eco-cultural differences between subset populations. Nonetheless, in terms of its relevance to diachronic considerations on niche evolution, it demonstrates that the general tendency throughout the
Neolithic Period is towards expansion of the eco-cultural niche rather than towards total niche replacement.
In the interest of establishing whether eco-cultural niches and cultural differences co- vary, I created two subset models for the Late Neolithic Period using Vinča B and
Topolnitsa/Akropotamos settlements. Settlements of the Strumsko and Galepsos types were excluded from this process for two reasons: (1) there are issues regarding their chronological affiliation as they may actually be more closely related with the Early Copper
Age transition; and (2) the number of settlements for these cultural groups is insufficient for the purposes of the modeling procedure. Furthermore, while the Topolnitsa and
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Akropotamos populations actually represent two distinguishable groups, an adequate sample size for modeling could only be obtained by their combination. This is reasonable given the considerable degree of similarity between their overall cultural assemblages— the Topolnitsa type having been described as a local variant of Akropotamos (Vajsov
2007). Possible discrepancies in the eco-cultural niche of the joint Topolnitsa/Akropotamos subset population will therefore be interpreted accordingly. The following section then elaborates on the more fine-grained characteristics of the Late Neolithic eco-cultural niche in light of subset populations and cultural diversification.
6.4.1 The Vinča B Late Neolithic subset eco-cultural niche
The Vinča B eco-cultural niche generally overlaps geographically with that of the Early
Neolithic Period and is confined to the Middle and Upper Struma Valleys. There are, however, some considerable differences in terms of the ecological dependencies. While the bioclimatic variables remain the same as during the Early Neolithic Period, with a moderate mean annual temperature, high temperature annual range, and low precipitation seasonality garnering the highest probability values, the terrain characteristics have notably shifted.
Vinča B settlements are more likely to be located on sloped terrains with a moderate topographic wetness index as opposed to flat terrains and a high topographic wetness index, which was the norm during the Early Neolithic Period. The probability values for different soil types have shifted as well, with vertisols now presenting a 10% greater probability for settlement. When taken in unison these characteristics indicate a significant movement into highland areas. Though the latter case may appear to indicate a shift in settlement pattern
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as the result of environmental change—presumed as increased humidity and wetter conditions in the lowlands (Genadieva 2007)—the continued occupation in the valley bottoms of settlements that were founded during the Early Neolithic Period paired alongside the emergence of new occupations in similar geographic locations creates a significant obstacle in terms of arguing in favour of the climate change hypothesis. Rather, a shift in subsistence practices and in agricultural niche construction may better substantiate the characteristics of the Vinča B eco-cultural niche.
Two particularly striking differences are apparent from the faunal assemblages of Vinča
B settlements in comparison with those from the Early Neolithic Period. First, there is an increase in the importance of cattle: they now approach 30% or more of the faunal assemblage at several settlements as opposed to an average of 15% during the Early
Neolithic Period. The second is an overall reduction in the use of wild resources (with the exception of Topolnitsa) with the presence of ungulates having reduced substantially.
When taken together with the characteristics of the Vinča B eco-cultural niche, I propose that the importance of stock breeding and cattle herding gained considerably. In this regard, the probability for upland settlement and restricted lowland settlement corresponds with occupations that are more suitable for grazing than for agriculture. Also, the first evidence of deforestation is noted during this Period (Marinova et. al 2012) and may coincide with the clearing of pasture lands leading to the reduced availability of medium sized game mammals in conjunction with the greater availability of medium sized domesticates.
Furthermore, the settlement pattern may also suggest the development of transhumance practices between upland and lowland sites. Although more evidence is needed to substantiate the claim of transhumance, the age profiles at Mursalevo indicate that cattle
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were being kept to greater maturity and the authors are lead to the conclusion that secondary animal products are perhaps now being exploited (Marinova et al. 2016). However, should a complimentary age profile of primarily juvenile individuals be recovered from upland sites, then the kill-off pattern might also suggest that mature individuals were culled in the lowlands prior to migration towards upland sites in the spring (Greenfield 1991).
Regardless of whether or not transhumance practices became an important aspect of the subsistence economy, the evidence most certainly points to the adoption of cattle herding and stock breeding as having taken precedence during this Period. For instance, the settlement of Topolnitsa located in the Middle Struma Valley and associated with Vinča B cultural elements in its early stages, bears evidence for the hybridization of domestic and wild cattle perhaps acting as a regional production center (Iliev and Spassov 2007).
Furthermore, a large dug-in sanctuary identified in Phases I & II of the settlement was decorated with several clay formed bucrania highlighting the increased importance of cattle in the material assemblage as well (Vajsov 2007). Similarly, at Damyanitsa—a large settlement surpassing 210 000 m2 in surface area—also located in the Middle Struma
Valley, the preliminary investigations of the early stages at the settlement have identified a proportion of more than 75% cattle in the faunal assemblage (De Cupere, unpublished).
Therefore, the eco-cultural niche of Vinča B settlements in conjunction with the evidence of a shift in subsistence practices strongly correlates with the episode of cultural diversification that occurred in the Upper and Middle Struma Valleys during the Late
Neolithic Period. Though the source of this change is still debated, it is plausible to suggest that the influence of Middle Neolithic practices—as was first identified by the diffusion of black polished ceramics towards the north—intensified and that stock breeding practices
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were also introduced to the region via similar lines of communication. In any case, and no matter the direction of influence, the result is the evolution of the eco-cultural niche towards the inclusion of more agriculturally marginal landscapes.
6.4.2 The Topolnitsa/Akropotamos Late Neolithic subset eco-cultural niche
The Topolnitsa/Akropotamos eco-cultural niche is geographically confined to the Middle and Lower Struma Valleys with only weak probability for settlement (40% or less) accorded to the north of Kresna Gorge. There is however considerable overlap between the
Vinča B and Topolnitsa/Akropotamos Late Neolithic niches in the Sandanski-Petrich Basin of the Middle Struma Valley, suggesting an adaptive trait that is mutual in both populations allowing for settlement in this sub-region. Ecological dependencies are near exclusively tied to high mean annual temperatures (70% probability in areas of 15 °C and decreasing to 0% at 8 °C), with all other variables contributing less than 10% in terms of model contribution and permutation importance. The ecological dependencies on all other variables except mean annual temperature should then correspondingly be interpreted with great caution.
With regards to the terrain characteristics, high probability values are accorded to flat terrains and on soils of the cambisol, fluvisol, regosol, and luvisol types. The dependencies on the bioclimatic characteristics are indicative of positive correlations with increasing precipitation seasonality and mean annual temperatures. Topographic wetness index and temperature annual range did not contribute to the model building process whatsoever and their values are potentially misleading and therefore will not here be addressed in
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consideration of the eco-cultural relationship. In general, however, the characteristics align strongly with Mediterranean and sub-Mediterranean climates. The 40% probability or less in continental type climates is, although possible, mitigated by the total absence of settlements of these types to the north of Kresna Gorge. The characteristics of the eco- cultural niche then points to regions with limited year-round agricultural potential situated primarily in the lowlands and valley bottoms of the Sandanski-Petrich and Drama Basins.
Einkorn is the dominant crop type on many settlements of the Topolnitsa/Akropotamos type and cattle represents on average 30% or more of the faunal assemblage. Furthermore, during the later stages of the Topolnitsa and Damyanitsa settlements—originally attributed to the Vinča B cultural group—the repertoire totally changes to that of the Topolnitsa type—a local variant of Akropotamos—following strong conflagration events suggesting the occurrence of partial population replacement in the Middle Struma Valley at that time.
Considering the noted importance of cattle at both of these settlements during their earlier stages, it is likely that they would have continued to serve the same or a similar economic purpose in their later stages. It is therefore also probable that the joint
Topolnitsa/Akropotamos eco-cultural niche defined by its affinity for Mediterranean type climates is actually representative of two separate niches—the first related to the
Akropotamos culture proper and confined to the Lower Struma Valley, and the second determined by the later manifestation of Topolnitsa type settlements presenting more similarities with the previous Vinča B eco-cultural niche in the Middle Struma Valley. In the absence of more numerous samples, however, it is for the moment impossible to identify the respective eco-cultural niches of each type. At the most, it could be advanced that Akropotamos settlements were located on marginal agricultural soils in the valley
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bottoms of the Drama Basin and close to river systems (inferred from the probability of flat terrains) and that they may have practiced year-round open plains stock breeding supplemented by improved agricultural techniques. The Topolnitsa settlements, on the other hand, are more closely in line with the Vinča B eco-cultural niche (in terms of their terrain and climate characteristics) and may have been influenced by the latter’s upland settlement system with limited occupation in the valley bottoms as the result of eco-cultural niche inheritance. Thus, by the end of the Late Neolithic Period, the Struma River Valley was characterized by at least two and possibly even three subset populations occupying partially mutually exclusive eco-cultural niches in each of the Struma River Valley’s sub- regions—namely Vinča B in the Middle and Upper Struma Valley, Topolnitsa in the south
Middle Struma Valley, and Akropotamos confined to the Lower Struma Valley. As the results of the generalized Late Neolithic eco-cultural niche demonstrate, however, they collectively occupied nearly all of the available inhabitable landscape in the region.
6.5 Diachronic considerations in eco-cultural niche evolution
Throughout the previous characterization of the Neolithic eco-cultural niches, I have discussed the consequences and impacts of niche overlap and niche breadth only in qualitative terms. In order to better quantify the degree of eco-cultural niche overlap and niche breadth between different periods, and to clarify its consequences and impacts in the process, I calculated niche overlap (Warren 2008) and niche breadth metrics (Levins 1968) for each of the eco-cultural niche models from the Neolithic Period in the Struma River
Valley (see Tables 13, 14, 15, & 16 on pgs. 103 & 104). Collectively, they serve to provide
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additional insight into the diachronic tendencies of eco-cultural niche evolution. All three niche overlap metrics (Schoener’s D, the I statistic, and relative rank; see Section 4.5.1) agree in general terms—albeit conferring different types of information based on the nature of the calculation. All of the eco-cultural niches overlap to some extent, suggesting the mutual ability of different populations to thrive in similar ecological conditions. The
Middle Neolithic eco-cultural niche overlaps most strongly with that of the Early Neolithic and the Late Neolithic eco-cultural niche overlaps considerably with that of the Middle
Neolithic—a result that should be expected given normal chronological progression. The
Vinča B Late Neolithic subset eco-cultural niche, however, overlaps most strongly with that of the Early Neolithic Period, while the joint Topolnitsa/Akropotamos eco-cultural niche is most aligned with that of the Middle Neolithic Period. Furthermore, the case in which niche overlap values are the least pronounced concerns the contemporary Late
Neolithic Vinča B and Topolnitsa/Akropotamos subset populations. The latter therefore indicates that differences in the eco-cultural relationship may have played a larger role in the distinction between these two Late Neolithic populations—the first apparently driven by changes to the Early Neolithic eco-cultural niche, and the second driven almost entirely by the conditions of the Middle Neolithic eco-cultural niche.
With regards to niche breadth, the latter indicates whether the eco-cultural niche of the population in question is highly specialized (i.e. restricted in comparison to the total available range of ecological conditions) or generalized (i.e. not restricted in comparison to the total available range of ecological conditions). According to the B1 Levins measure, the Early Neolithic eco-cultural niche occupies 35% of the total ecological variability in the Struma River Valley, the Middle Neolithic occupies 39%, and the Late Neolithic
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occupies 48%. The general tendency then is towards increasing occupation of the total ecological variability and towards eco-cultural niche generalization over time. Considering the two Late Neolithic subset populations, however, we see that the Vinča B eco-cultural niche occupies 32% of the total ecological variability and that the Topolnitsa/Akropotamos eco-cultural niche is even more restricted composing only 28% of the total ecological variability. Interestingly, both are also slightly more restricted (i.e. specialized) than was the Early Neolithic eco-cultural niche. Therefore, while there is a general tendency towards expanded occupation of the total ecological variability over time, in the Late Neolithic the latter is only achieved by compounding the effects of two or more diametrically opposed specialist niches. The paradox here to consider is that cultural diversification events resulting from eco-cultural niche inheritance then actually may have served to expand on the carrying capacity of the landscape. In other words, the co-occurrence of several specialized eco-cultural niches may in fact make more efficient use of the total ecological variability present on the landscape better than could any single generalist eco-cultural niche. During the Neolithic of the Struma River Valley, at least, it appears that episodes of eco-cultural niche diversification were compounded with the result of accommodating probable demographic expansion via the reconstruction of the early agricultural niche.
6.6 The relationship between culture and ecology during the Neolithic Period
In summary, the interpretation of the Neolithic eco-cultural niches in the Struma River
Valley has provided valuable insight into the relationship between culture and ecology and its impacts on the cultural evolutionary process. First, the Early Neolithic niche was rather
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specialized to include prime and easily worked agricultural lands in the temperate and sub-
Mediterranean zone and was therefore limited in terms of expansion. Nonetheless, the more marginal characteristics of the Early Neolithic eco-cultural niche have highlighted a tendency towards the mitigation of local ecological conditions via the reconfiguration of the early agricultural assemblage towards the occupation of more marginal landscapes.
Second, during the Middle Neolithic Period it is probable that stock-breeding gained in importance allowing for an expansion to the eco-cultural niche. The latter is also associated with limited episodes of cultural diversification exemplified by the different variants of black polished pottery found in each of the Struma River Valleys sub-regions. The intensification of stock-breeding practices in the agricultural repertoire of the region then may have led towards the increased occupation of more marginal agricultural lands in the
Middle Struma Valley and later into the Lower Struma Valley as well, effectively increasing competitive fitness and also modifying natural selection pressures. Following the Middle Neolithic Period, cultural diversification is far more evident during the Late
Neolithic Period and operates almost exclusively in line with changes to the eco-cultural relationship that were first introduced during the Middle Neolithic. Cattle and stock breeding are now of increasing importance throughout the entire Struma River Valley, although possibly managed in two different ways based on the varied ecological characteristics in each of the Struma River Valley’s sub-regions. The Vinča B and
Topolnitsa/Akropotamos populations, despite their overlapping contact zone in the Middle
Struma Valley, occupy near diametrically opposed specialized eco-cultural niches that only when taken in unison actually expand on the total occupied landscape. It then appears that episodes of cultural diversification and the multiplication of specialized eco-cultural niches
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paradoxically lead towards the increased competitive fitness of Neolithic communities in the Struma River Valley in general and accommodated demographic expansion.
A static observation of each period may at first give the impression that subsistence practices are perfectly adapted to the environmental conditions in which they are located, leading towards the erroneous conclusion that environmental selection pressures played a more important role on the cultural evolutionary process than was probably actually the case. The diachronic evaluation of the Neolithic eco-cultural niches rather shows that subsistence practices were modified first via the reconstruction of the early agricultural niche based primarily on cultural and historical contingencies, which then mitigated natural selection pressures allowing for expansion into more agriculturally marginal landscapes and ultimately increasing competitive fitness. The occupation of new environments and more agriculturally marginal landscapes then was the result rather than the cause of agricultural niche diversification. With selection pressures mitigated, expansion into previously unoccupied regions ensued and was followed by more frequent episodes of cultural change. By the end of the Late Neolithic Period, the latter was exemplified by the presence of two and possibly even three subset populations—Vinča B, Topolnitsa, and
Akropotamos—each characterized by its own cultural repertoires and confined to each of the Struma River Valley’s sub-regions. It may then be concluded that the evolution of cultural variability was at least in part driven by the ecological setting of the Struma River
Valley and by differentiation in the evolution of the early agricultural niche.
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Chapter 7 – Conclusion Agriculture as niche construction
7.1 Agriculture as niche construction
As niche construction theory (NCT) argues, organisms do not simply live within their environments. Rather, organisms can actively modify natural selection pressures via niche construction and thereby direct their own evolutionary process (Odling-Smee et al. 2003).
With regards to humans more specifically, our uniquely elaborate cultural repertoires are in constant interaction with the environment, which may in fact make us the most potent niche constructors of all (Laland and O’Brien 2010; Odling-Smee et al. 2003; Odling-Smee and Laland 2012; Smith 2007a). The relationship between culture and ecology is reciprocal.
In the case of the Struma River Valley, I have demonstrated how the introduction and subsequent reconstruction of the early agricultural niche during the Neolithic Period may be taken as a niche construction event that bore significant evolutionary consequences. I conclude that the evolution of cultural variability in the region was then at least in part driven by the ecological setting of the Struma River Valley and more importantly by the reconstruction of the early agricultural niche. Furthermore, I found that cultural and historical contingencies played an equally important role on the evolution of populations and that ecological factors alone cannot account for the numerous episodes of cultural diversification that occurred in the region.
The introduction of agriculture to the Struma River Valley first allowed populations to expand over the landscape and exploit environments that were conducive to the northward
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spread of early agricultural domesticates (Marinova 2007). In a sense, the Early Neolithic populations were then pre-adapted for life in the Valley within a well-defined eco-cultural niche—that is to say, an eco-cultural niche that was ideal for growing a wide arrangement of pre-existing crop types. However, I also argue based on the results of the Early Neolithic eco-cultural niche that populations could expand into more marginal landscapes via the reconfiguration of their agricultural assemblage. In fact, the continuous reconstruction of the agricultural niche all throughout the Neolithic Period in the Struma River Valley, as is exemplified by the increased importance of cattle herding and stock breeding during the
Middle and Late Neolithic Periods, allowed for populations to expand even further into new eco-cultural niches that presented distinct selection pressures and thereby stimulated the evolutionary process to an even greater extent. Cultural and ecological selection pressures, with niche construction acting as an intermediary, then converged to ultimately produce the array of cultural diversity found within the region, from an originally relatively undiversified cultural base to heightened cultural variability between different ecological sub-regions over time. Therefore, the evolution of Neolithic societies in the Struma River
Valley can be better understood only when considering agriculture as a niche construction event.
7.2 Directions for future research
While the primary concern of this work was to investigate the impact of niche construction on the cultural evolutionary process, it can be reasonably suggested that the eco-cultural niche models here presented could also be utilized for different purposes and to an even
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greater extent. As was discussed by Galletti et al. (2013), the characteristics of the eco- cultural niche can also be used to infer any number of additional relationships between culture and the environment. The following sub-sections then serve to outline some potential directions for future research both specifically with regards to the current study and more generally with regards to the relationship between niche construction and the eco- cultural niche.
7.2.1 In consideration of different ecological variables
In this thesis, I selected a very specific set of ecological variables for the production of the eco-cultural niche models. I chose them firstly based on their ease of availability and in consideration of their relationship to the primary subsistence practice of the Neolithic
Period. However, there are of course a great number of other ecological variables not here considered that may provide some additional insight into the relationship between culture and environment. For instance, datasets concerning surface geology, proximity to rivers, humidity, vegetational landcover, susceptibility to inundation and other natural disasters, etc., could be used to refine and/or elaborate on the eco-cultural niches of Neolithic populations even further. Such reanalyses could then potentially provide useful information in terms of settlement location selection. While my argument has focused more specifically on correlative factors between ecology, culture, and subsistence, through the use of more elaborate datasets one could also potentially advance reasonable causal explanations with regards to settlement distribution and location more specifically.
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7.2.2 In consideration of additional cultural variables
The populations that I defined in this study were primarily identified by commonalities in their cultural assemblage—namely by decorative pottery types and subsistence practices— and in their chronological association across sites. There are of course other cultural traits that may prove worthwhile investigating in terms of the relationship between culture and ecology. Architectural features, storage contexts, preferred raw materials, wild faunal assemblages, and vessel petrography, are but a few examples that could each also be potentially related to considerations of the eco-cultural niche. Particular types of architectural features such as pitched roofs and their ability to direct water runoff, for instance, may perhaps be found to correlate with areas of high precipitation while perhaps later may also correlate with regions of lower precipitation in which their original functional intent may no longer be of significant importance. Not only would such types of analyses prove interesting between distinguishing different populations and cultural developments, but they could also shed some light on differences within a single population at both the intra and inter-settlement scales. Additionally, the identification of such cultural traits in reference to the eco-cultural niche could also be used to determine to what extent ecology regulates particular cultural expressions irrespective of chronology and/or of specific population.
7.2.3 In consideration of niche construction
By taking the example here provided of agriculture as niche construction in the Struma
River Valley, we can potentially also elaborate on the role of niche construction in the
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cultural evolutionary process more generally and with regards to other populations in different archaeological contexts. In this thesis, agriculture has been identified as a particular type of niche construction event that bears definite evolutionary consequences.
Exploring the effects of agriculture as a niche construction event in other archaeological contexts may then also prove fruitful and serve to expand on the conclusions here reached.
There are, however, other types of niche construction that could equally have affected the evolution of particular populations. By identifying the ecological characteristics of settlements, the natural selection pressures at those locations can also be inferred and a study undertaken to determine if and/or how the community mitigated or guarded against their particular ecological circumstances. For example, should the eco-cultural niche be identified with areas of high flood potential, how did the communities thrive in that environment and what kinds of technologies did they employ? Or, if they were located in areas of low soil fertility, how was agriculture practiced and how did the presence of those agricultural practices affect the landscape in the long term? Furthermore, according to niche construction theory (NCT), the continuous and compounded effects of niche construction can lead to a permanent change in the local environment and ultimately to what has been termed ecological inheritance (Odling-Smee 1988; Odling-Smee and Laland 2012). A diachronic evaluation of ecological inheritance then can be used to elaborate on how societies were impacted and adapted in relation to self-induced change in their local environments from an eco-cultural niche perspective.
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7.2.4 In consideration of directionality, cultural contacts, and potential for movement
With regards to the current study more specifically, it has been explicitly stated that the
Struma River Valley during the Neolithic Period did not exist in isolation from its neighbouring regions. Low lying mountain passes connect the Struma River Valley with all of the neighbouring regions, including the Vardar/Axios Valley to the west, the
Mesta/Nestos Valley to the east, the Sofia Basin to the north, the region of West Greek
Macedonia to the southwest, and with Turkish and Aegean Thrace to the southeast. By projecting the eco-cultural niche models here produced onto the larger surrounding landscape, potential connections between the Neolithic cultures of the Struma River Valley and the neighbouring regions can be determined from a correlational eco-cultural niche point of view and also used to elaborate on issues of directionality, cultural contact, and movement. In fact, several cultural parallels have been recognized between each of the broader regions (see Demoule 2009; Pernicheva-Perets et al. 2011; Tsirtsoni 2016 for relevant examples) and it would be useful to investigate whether or not those particular cultural parallels are correlated in terms of similarities between their respective eco-cultural niches.
7.3 Conclusion
This thesis has been directly informed by the concepts of the eco-cultural niche and of niche construction. I initially sought to determine whether recent developments on modeling the eco-cultural niche, in its characterization of the reciprocal relationship between culture and the environment, could be applied as an analytical tool towards elaborating on the effects
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of niche construction. I found that such an approach is in fact viable and that by investigating the effects of niche construction through the lens of the eco-cultural niche a number of important evolutionary consequences can be revealed. The latter is made most evident within the current work by the identification of agriculture as a niche construction event during the Neolithic of the Struma River Valley, which was assessed against a backdrop of diachronic change to the eco-cultural niche. In conclusion, several key considerations with regards to the eco-cultural niche and niche construction discussed within the literature may now be more thoroughly supported.
First, as Galletti et al. (2013) advanced, eco-cultural niche models can in fact be used to yield valuable information with regards to changes in landscape selection based on particular subsistence practices and additional cultural factors. Second, as Banks and colleagues (2013) demonstrated, eco-cultural niche models can also be used to help define the reciprocal relationship between population, culture, and environment, ultimately providing a framework under which cultural adaptations (such as niche construction) may be evaluated in light of environmental, historical and, cultural contingencies. Third, as
Rowley-Conwy and Layton (2011) argue, agriculture as a culturally constructed niche must be continuously reconstructed in response to its own inherent instability. As the reconstructed agricultural niche is then exported, populations must adapt to their new environments and ecological selection pressures further directing the evolutionary process and leading to additional occurrences of agricultural niche construction (Rowley-Conwy and Layton 2011). And fourth, as Smith (2007b) suggested, it is not only reasonable but necessary to conclude that niche construction—as a ubiquitous underlying human behavioural framework—has played a role in the evolution of human societies generally.
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To assume otherwise is to ignore the ever-increasing body of evidence that attests to the reciprocal nature of the relationship between humans, culture, and the environment. The local contingencies of niche construction, however, depend on the particular relationship between culture and environment at specific times and in specific places and by identifying the eco-cultural niche at those specific times and places, a framework is provided under which the local contingencies of niche construction can be better understood.
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References Cited
Гребска-Кулова, M. 2009 Теренни Археологически Обхождания в Благоевград-ската Общинал [Archaeological Surveys in the Blagoevgrad Basin Municipality]. Известия на Регионален Исторически Mузей Благоевград [Notifications from the Blagoevgrad Regional History Museum], Vol. 5. Pp. 37-52.
Anderson, Robert P., and Ali Raza 2010 The Effect of the Extent of the Study Region on GIS Models of Species Geographic Distributions and Estimates of Niche Evolution: Preliminary Tests with Montane Rodents (Genus Nephelomys) in Venezuela. Journal of Biogeography 37:1378-1393.
Banks, William E., Francesco d’Errico, Harrold L. Dibble, Leonard Krishtalka, Dixie West, Deborah I. Olszewski, A. Townsend Peterson, David G. Anderson, J. Christopher Gillam, Anta Montet-White, Michel Crucifix, Curtis W. Marean, María-Fernanda Sánchez-Goñi, Barbara Wohlfarth, and Marian Vanhaeran 2006 Eco-Cultural Niche Modeling: New Tools for Reconstructing the Geography and Ecology of Past Human Populations. Paleoanthropology 2006:68-83.
Banks, William E., Francesco d’Errico, A. Townsend Peterson, Marian Vanhaeren, Masa Kageyama, Pierre Sepulchre, Gilles Ramstein, Anne Jost, Daniel Lunt 2008 Human Ecological Niches and Ranges During the LGM in Europe Derived From an Application of Eco-Cultural Niche Modelling. Journal of Archaeological Science 35:481-491.
Banks, William E., Nicolas Antunes, Solange Rigaud, and Francesco d’Errico
P a g e | 135
2013 Ecological Constraints on the First Prehistoric Farmers in Europe. Journal of Archaeological Science 40:2746-2753.
Barbet-Massin, Morgane, Frédéric Jiguet, Cécile Hélène Albert, and Wilfrid Thuiller 2012 Selecting Pseudo-Absences for Species Distribution Models: How, Where, and How Many? Methods in Ecology and Evolution 3:327-338.
Berger, Jean-François, and Jean Guilaine 2009 The 8200 cal BP Abrupt Environmental Change and the Neolithic Transition: a Mediterranean Perspective. Quaternary International 200:31-49.
Bevan, A., and J. Conolly 2011 Terraced Fields and Mediterranean Landscape Structure: An Analytical Case- Study From Antikythera, Greece. Ecological Modelling 222:1303-1314.
Bojadžiev, J. 2007 Absolute Chronology of the Neolithic and Eneolithic Cultures in the Valley of Struma. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 309-316. Sofia: Gerda- Henkel-Stiftung.
Bökönyi, Sàndor, with D. Jànossy 1986 Faunal Remains. In Excavations at Sitagroi: A Prehistoric Village in Northeast Greece Volume 1. edited by Colin Renfrew, Marija Gimbutas, and Ernestine S. Elster. Pp. 63-132. Los Angeles: Cotsen Institute of Archaeology, University of California.
P a g e | 136
Boyadziev, Yavor D. 1995 Chronology of Prehistoric Cultures in Bulgaria. In Prehistoric Bulgaria. Monographs in World Archaeology No 22. edited by D. Bailey and I. Panayotov with Stefan Alexandrov, Pp. 149-191. Madison, Wisconsin: Prehistory Press.
Boyd, Robert, and Peter J. Richerson 1985 Culture and the Evolutionary Process. University of Chicago Press.
Brace, C. Loring 1967 The Stages of Human Evolution: Human and Cultural Origins. Englewood Cliffs: Prentice-Hall
Burrough, Peter A., and Rachael A. McDonell 1998 Principles of Geographical Information Systems. Oxford: Oxford University Press.
Butzer, Karl W. 1971 Environment and Archaeology: An Ecological Approach to Prehistory. London: Methuen.
Chohadzhiev, Stefan 2007 Neolithic and Chalkolithic Cultures in the Struma River Basin. Veliko Tarnovo.
Čochadžiev, Stefan, Aneta Bakamska, and Lazar Ninov 2007 Krajnici—An Early-Pottery Settlement in the Strouma Valley. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich,
P a g e | 137
and Georgi Ivanov, Pp. 182-190. Sofia: Gerda-Henkel-Stiftung.
Čohadžiev, S. 1998 James Harvey Gaul and the Studies of the Neolithic and Eneolithic in Western Bulgaria. In In the Steps of James Harvey Gaul, Vol. 1. edited by Mark Stefanovich, Henrieta Todorova, and Harald Hauptmann, Pp. 93-78. Sofia: The James Harvey Gaul Foundation.
Conolly, James, Katie Manning, Sue Colledge, Keith Dobney, and Stephen Shennan 2012 Species Distribution Modelling of Ancient Cattle from Early Neolithic Sites in SW Asia and Europe. The Holocene 22(9):997-1010.
Davis, B. A. S., S. Brewer, A. C. Stevenson, and J. Guiot, with data contributors 2003 The Temperature of Europe During the Holocene Reconstructed from Pollen Data. Quaternary Science Reviews 22:1701-1716.
Dawkins, R. 2004 Extended Phenotype—But not too Extended. A Reply to Laland, Turner and Jablonka. Biological Philosophy 19:377-396.
Demoule, Jean-Paul, and Catherine Perlès 1993 The Greek Neolithic: A New Review. Journal of World Prehistory 7(4):355- 416.
Demoule, Jean-Paul 2009 La Colonisation de l’Europe Balkanique: Chronologie et Processus. In De Méditerranée et d’Ailleurs: Mélanges Offerts à Jean Guilaine, Pp. 251-268.
P a g e | 138
Toulouse: Archives d’Écologie Préhistorique.
Elith, Jane, Michael Kearney, and Steven Phillips 2010 The Art of Modelling Range Shifting Species. Methods in Ecology and Evolution 1:330-342.
Galletti, Christopher S., Elizabeth Ridder, Steven E. Falconer, Patricia L. Fall 2013 Maxent Modelling of Ancient and Modern Agricultural Terraces in the Troodos Foothills, Cyprus. Applied Geography 39:46-56.
Genadieva, V. 2007 Prehistoric Settlements in the Province of Kjustendil. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 239-246. Sofia: Gerda-Henkel-Stiftung.
Georgiev, G. I. 1961 Kulturgruppen der Jungstein-und der Kuperzeit in der Ebene von Thrazien (Südbulgarien). In L’Europe à la fin de l’Âge de la Pierre. edited by J. Böhm and S. J. De Laet, Pp. 45-100. Prague.
Gessler, P. E., I. D. Moore, N. J. McKenzie, and P.J. Ryan 1995 Soil Modeling and Spatial Prediction of Soil Attributes. International Journal of GIS 9(4):421-432.
Gimbutas, Marija 1974 Anza, ca. 6500-5000 B. C.: A Cultural Yardstick for the Study of Neolithic Southeast Europe. Journal of Field Archaeology 1(1/2):26-66.
P a g e | 139
Grębska-Kulova, Malgorzata 2003 Balkan Anatolian Relations in the Late Neolithic (Second Half of the 6th mill. BC). АРХЕОЛОГИЯ 3:5-15.
Grębska-Kulova, M. 2004 Cultural Changes in the Second Half of the 6th Mill. BC in Southwestern Bulgaria. In Prehistoric Thrace. edited by V. Nikolov, K Băčvarov, and P. Kalchev, Pp. 133-145. Sofia-Stara Zagora.
Grębska-Kulowa, M., and I. Kulow 2007 Prehistorical Sites in the Middle Struma River Valley Between the End of the VIIth Mill. BC and the Beginning of the Ist Mill. BC. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 279-296. Sofia: Gerda-Henkel-Stiftung.
Greenfield, Haskel J. 1991 Fauna from the Late Neolithic of the Central Balkans: Issues in Subsistence and Land Use. Journal of Field Archaeology 18(2):161-186.
Grinnell, Joseph 1917 The Niche-Relationships of the California Thrasher. The Auk 34(4):427-433.
Hutchinson, G. Evelyn 1957 A Treatise on Limnology, vol. 1 Geography, Physics and Chemistry. Wiley.
Iliev, Nilolai, and Nikolai Spassov 2007 Promachon-Topolnica Comparative Study of the Domestic and Wild Animals
P a g e | 140
from the Sector Topolnica. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 509-522. Sofia: Gerda-Henkel-Stiftung.
Kendal, Jeremy, Jashmid J. Tehrani, and John Odling-Smee 2011 Human Niche Construction in Interdisciplinary Focus. Theme Issue, “Human Niche Construction”, Philosophical Transactions of the Royal Society B 366(1566):785-792.
Kluiving, Sjoerd J. 2015 How Geoarchaeology and Landscape Archaeology Contribute to Niche Construction Theory (NCT). Water History 7:557-571.
Koukouli-Chryssanthaki, Haïdo, René Treuil, Laurent Lespez, and Dimitra Malamidou 2008 Dikili Tash, Village Préhistorique de Macédoine Orientale—Recherches Franco-Hélléniques Dirigées par la Société Archéologique d’Athènes et l’École Française d’Athènes (1986-2001) [Dikili Tash Prehistoric Village of East Macedonia—Franco-Hellenic Research Project Directed by the Archaeological Society of Athens and the French School of Athens]. Athènes:
Bibliothèque de la Société Archéologique D’Athènes N⁰ 254.
Kreuz, Angela, Elena Marinova, Eva Shäfer, and Julian Wiethold 2005 A Comparison of Early Neolithic Crop and Weed Assemblages from the Linearbandkeramic and the Bulgarian Neolithic Cultures: Differences and Similarities. Vegetation, History, and Archaeobotany 14:237-258.
Laland, Kevin N., and Michael J. O’Brien
P a g e | 141
2010 Niche Construction Theory and Archaeology. Journal of Archaeological Method and Theory 17:303-322.
Lambeck, Kurt, and Anthony Purcell 2005 Sea-Level Change in the Mediterranean Sea Since the LGM: Model Predictions for Tectonically Stable Areas. Quaternary Science Reviews 24:1969-1988.
Lee, R. 1980 Lactation, Ovulation, Infanticide, and Women’s Work: a Study of Hunter- Gatherer Population Regulation. In Biosocial Mechanisms of Population Regulation. edited by N. M. Cohen, R. Malpass, and H. Klein. Pp. 321-348. New Haven, CT: Yale University Press
Levins, R. 1968 Evolution in Changing Environments. Monographs in Population Biology Volume 2. Princeton: Princeton University Press.
Marinova, E. 2006 Archaeobotanical Studies of the Bulgarian Neolithic. The Current State of Research and Perspectives for Future Study. In Aegean—Marmara—Black Sea: The Present State of Research on the Early Neolithic. edited by I. Gatsov and H. Schwarzberg. Pp. 187-194. Langenweissbach: Beier & Beran.
Marinova, Elena 2007 Archaeobotanical Data from the Early Neolithic of Bulgaria. In The Origins and Spread of Domestic Plants in Southwest Asia and Europe. edited by Sue Colledge and James Conolly, Pp. 93-109. Walnut Creek: Left Coast Press, Inc..
P a g e | 142
____ 2009 Plant Economy and Vegetation During the Early Neolithic of Bulgaria. In The First Neolithic Sites in Central/South-East European Transect Volume I: Early Neolithic Sites on the Territory of Bulgaria. edited by Ivan Gatsov and Yavor Boyadzhiev. Pp. 59-62. Bar International S2048.
Marinova, Elena, and Stephanie Thiebault 2008 Anthrocological Analysis from Kovacevo, Southwest Bulgaria: Woodland Vegetation and Its Use During the Earliest Stages of the European Neolithic. Vegetation, History, and Archaeobotany 17:223-231.
Marinova, Elena, Spassimir Tonkov, Elissaveta Bozilova, and Ivan Vajsov 2012 Holocene Anthropogenic Landscapes in the Balkans: The Paleobotanical Evidence from Southwestern Bulgaria. Vegetation, History and Archaeobotany. accessed June 4th, 2012, DOI 10.1007/s00334-011-0345-8.
Marinova, Elena, and Soultana-Maria Valamoti 2014 Crop Diversity and Choice in the Prehistoric South-Eastern Europe: Cultural and Environmental Factors Shaping the Archaeobotanical Record of Northern Greece and Bulgaria. In Plants and People: Choices and Diversity Through Time. edited by Alexandre Chevalier, Elena Marinova, and Leonor Peña- Chocaro. Pp. 64-74. Oxford: Oxbow Books.
Marinova, Elena, Bea De Cupere, and Vassil Nikolov 2016 Preliminary Results of the Bioarchaeological Research at the Neolithic Site Mursalevo (South-West Bulgaria): Evidence on Food Storage, Processing and Consumption from Domestic Contexts. In Southeast Europe and Anatolia in
P a g e | 143
Prehistory: Essays in Honor of Vassil Nikolov on his 65th Anniversary. edited by Krum Bacvarov and Ralk Gleser. Pp. 509-518. Bonn: Dr. Rudolf Habelt GmbH.
Moore I. D., R. B. Grayson, and A. R. Ladson 1991 Digital Terrain Modelling: A Review of Hydrological, Geomorphological, and Biological Applications. Hydrological Processes 5:3-30.
Muscarella, Robert, Peter J. Galante, Mariano Soley-Guardia, Robert A. Boria, Jamie M. Kass, María Uriarte, and Robert P. Anderson
2014 ENMeval: An R package for Conducting Spatially Independent Evaluations and Estimating Optimal Model Complexity for Maxent Ecological Niche Models. Methods in Ecology and Evolution 5:1198-1205.
Nikolov, Vassil 2007 Problems of the Early Stages of the Neolithization in the Southeast Balkans. In A Short Walk Through the Balkans: the First Farmers of the Carpathian Basin and Adjacent Regions. edited by Michela Spataro and Paolo Biagi. Pp. 183- 188. Trieste, Quaderno: Società Preistoria Protostoria Friuli-V.G.
Odling-Smee, John F. 1988 Niche-Constructing Phenotypes. In The Role of Behaviour in Evolution. edited by H. C. Plotkin. Pp. 73-132. Cambridge: MIT Press.
Odling-Smee, John F., Kevin N. Laland, and Marcus W. Feldman 2003 Niche Construction: The Neglected Process in Evolution. Princeton: Princeton University Press.
P a g e | 144
Odling-Smee, John, and Kevin N. Laland 2012 Ecological Inheritance and Cultural Inheritance: What Are They and How do They Differ? Biological Theory 2011(6):220-230.
Pavlopoulos, Kosmas 2012 Relative Sea Level Fluctuations in Aegean Coastal Areas From Middle to Late Holocene. Geodinamica Acta 23(5-6):225-232.
Perlès, Catherine 2001 The Early Neolithic in Greece: The First Farming Communities in Europe. Cambridge: Cambridge University Press.
Perničeva, L. 1983 Prehistory of the Strumešnica Valley. In The Lower Strumešnica Valley in Prehistoric, Ancient, and Early Medieval Times. edited by J. Śliwa and M. Domaradzki, Pp. 11-34. Kraków.
Perničeva, Liljana 2007 La Périodisation des Sites Préhistoriques de la Vallée de la Strouma Moyenne. [Periodisation of Prehistoric Sites in the Middle Struma Valley] In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 209-222. Sofia: Gerda-Henkel-Stiftung.
Pernicheva, Lilyana 1995 Prehistoric Cultures in the Middle Struma Valley: Neolithic and Eneolithic. In Prehistoric Bulgaria. Monographs in World Archaeology No 22. edited by D. Bailey and I. Panayotov with Stefan Alexandrov, Pp. 99-147. Madison,
P a g e | 145
Wisconsin: Prehistory Press.
Pernicheva-Perets, L., M. Grębska-Kulow, and I. Kulov 2011 Balgarchevo: the Prehistoric Settlement, Volume 1. Sofia: Craft House Bulgaria.
Peterson, A. Townsend 2011 Ecological Niches and Geographic Distributions. Princeton: Princeton University Press.
Peyron, Odile, Simon Goring, Isabelle Dormoy, Ulrich Kotthoff, Jörg Pross, Jacques- Louis de Beaulieu, Ruth Drescher-Schneider, Boris Vannière, and Michel Magny 2011 Holocene Seasonality Changes in the Central Mediterranean Region Reconstructed from the Pollen Sequences of Lake Accesa (Italy) and Tenaghi Phillipon (Greece). The Holocene 21(1):131-146.
Phillips, Steven J. Robert P. Anderson, and Robert E. Schapire 2006 Maximum Entropy Modeling of Species Geographic Distributions. Ecological Modelling 190(3-4):231-259.
Phillips, Steven J., and Miroslav Dudik 2008 Modeling of Species Distributions with Maxent: New Extensions and a Comprehensive Evaluation. Ecography 31:161-175.
Popova, Tz., And E. Marinova 2007 Paleobotanical Data in South-Western Region of Bulgaria. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich,
P a g e | 146
and Georgi Ivanov, Pp. 499-508. Sofia: Gerda-Henkel-Stiftung.
Popova, Tzvetana 2010 Plant Environment of Man between 6000 and 2000 B.C. in Bulgaria. Bar International Series S2064.
Pross, J., U. Kothoff, U. C. Müller, O. Peyron, I. Dormoy, G. Schmiedl, S, Kalaitzidis, and A. M. Smith 2009 Massive Perturbation in Terrestrial Ecosystems of the Eastern Mediterranean Region Associated with the 8.2 kyr B.P. Climatic Event. Geology 37(10):887- 890.
Pross, Jörg, Andreas Koutsodendris, Kimon Christanis, Tobias Fischer, William J. Fletcher, Mark Hardiman, Stavros Kalaitzidis, Maria Knipping, Ulrich Kotthoff, Alice M. Milner, Ulrich C. Müller, Gerhard Schmiedl, George Siavalas, Polychronis C. Tzedachis, and Sabine Wulf 2015 The 1.35-Ma-Long Terrestrial Climate Archive of Tenaghi Phillipon, Northeastern Greece: Evolution, Exploration, and Perspectives for Future Research. Newsletters on Stratigraphy 48(3):253-276.
Rackham, Oliver 1986 Appendix A: Charcoal. In Excavations at Sitagroi: A Prehistoric Village in Northeast Greece Volume 1. edited by Colin Renfrew, Marija Gimbutas, and Ernestine S. Elster. Pp. 55-62. Los Angeles: Cotsen Institute of Archaeology, University of California.
R Core Team 2015 R: A Language and Environment for Statistical Computing. R Foundation for
P a g e | 147
Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Renfrew, Colin, Marija Gimbutas, and Ernestine S. Elster, eds 1986 Excavations at Sitagroi: A Prehistoric Village in Northeast Greece, Vol. 1. Los Angeles: Cotsen Institute of Archaeology, University of California.
Renfrew, Jane M. 2003 Grains, Seeds, and Fruits from Prehistoric Sitagroi. In Prehistoric Sitagroi: Excavations in Northeast Greece, 1968-1970 Volume 2: The Final Report. edited by Ernestine S. Elster and Colin Renfrew. Pp. 3-30. Los Angeles: Cotsen Institute of Archaeology, University of California.
Rendell, Luke, Laurel Fogarty, and Kevin N. Laland 2011 Runaway Cultural Niche Construction. Theme Issue, “Human Niche Construction”, Philosophical Transactions of the Royal Society B 366(1566):823-835.
Riede, Felix 2011 Adaptation and Niche Construction in Human Prehistory: a Case Study from the Southern Scandinavian Late Glacial. Theme Issue, “Human Niche Construction”, Philosophical Transactions of the Royal Society B 366(1566):793-808.
Riley, Shawn J., Stephen D. DeGloria, and Robert Elliot 1999 A Terrain Ruggedness Index That Quantifies Topographic Heterogeneity. Intermountain Journal of Sciences. 5(1-4):23-27.
P a g e | 148
Rowley-Conwy, Peter, and Robert Layton 2011 Foraging and Farming as Niche Construction: Stable and Unstable Adaptations. Theme Issue, “Human Niche Construction”, Philosophical Transactions of the Royal Society B 366(1566):849-862.
Schoener, T. W. 1968 Anolis Lizards of Bimini: Resource Partitioning in a Complex Fauna. Ecology 49:704-726.
Scott-Phillips, Thomas C., Kevin N. Laland, David M. Shuker, Thomas E. Dickins, and Stuart A. West 2014 The Niche Construction Perspective: A Critical Appraisal. Evolution 68(5):1231-1243.
Shennan, Stephen 2000 Population, Culture History, and the Dynamics of Culture Change. Current Anthropology 41(05):811-835.
____ 2011 Property and Wealth Inequality as Cultural Niche Construction. Theme Issue, “Human Niche Construction”, Philosophical Transactions of the Royal Society B 366(1566):918-926.
Smith, Bruce D 2007a The Ultimate Ecosystem Engineers. Science, New Series 315(5820):1797- 1798.
P a g e | 149
____ 2007b Niche Construction and the Behavioral Context of Plant and Animal Domestication. Evolutionary Anthropology 16:188-199.
____
2009 Core Conceptual Flaws in Human Behavioral Ecology. Communicative & Integrative Biology 2(6):1-2.
Stefanova, Ivanka, and Brigitta Ammann 2003 Lateglacial and Holocene Vegetation Belts in the Pirin Mountains (Southwestern Bulgaria). The Holocene 13(1):97-107.
Steward, Julian 1955 Theory of Culture Change: The Methodology of Multilinear Evolution. Urbana: University of Illinois Press.
Tonkov, S. 2003 A 5000-Year Pollen Record from Osogovo Mountains, Southwestern Bulgaria. In Aspects of Palynology and Palaeoecology. edited by S. Tonkov. Pp. 233- 244. Sofia: Pensoft.
Tsirtsoni, Zoï, ed. 2016 The Human Face of Radiocarbon: Reassessing Chronology in Prehistoric Greece and Bulgaria 5000-3000 cal BC. Lyon: Maison de l’Orient et de la Méditerranée.
P a g e | 150
Vacchi, Matteo, Alessio Rovere, Alexandros Chatzipetros, Nickolas Zouros, and Marco Firpo 2014 An Updated Database of Holocene Relative Sea Level Changes in NE Aegean Sea. Quaternary International 328-329:301-310.
Vajsov, I. 2007 Promachon-Topolnica. A Typology of Painted Decorations and Its Use as a Chronological Marker. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 79-120. Sofia: Gerda-Henkel-Stiftung.
Valamoti, Soultana Maria 2007 Agriculture and Use of Space at Promachon/Topolnica. Preliminary Observations on the Archaeobotanical Material. In In the Steps of James Harvey Gaul, Vol. 2, edited by Henrieta Todorova, Mark Stefanovich, and Georgi Ivanov, Pp. 523-529. Sofia: Gerda-Henkel-Stiftung.
Valamoti, Soultana-Maria 2015 Harvesting the ‘Wild’? Exploring the Context of Fruit and Nut Exploitation at Neolithic Dikili Tash, with Special Reference to Wine. Vegetation, History, and Archaeobotany 24:35-46 van der Vaart, A. W. 1998 Asymptotic Statistics. Cambridge: Cambridge University Press.
Warren, Dan L., Richard E. Glor, and Michael Turelli 2008 Environmental Niche Equivelancy Versus Conservatism: Quantitative
P a g e | 151
Approaches to Niche Evolution. Evolution 62(11):2868-2883.
Warren, Dan L., and Stephanie N. Seifert 2011 Ecological Niche Modeling in Maxent: The Importance of Model Complexity and the Performance of Model Selection Criteria. Ecological Applications 21(2):335-342.
Weninger, Bernhard, Eva Alram-Stern, Eva Bauer, Lee Clare, Uwe Danzeglocke, Olaf Jöris, Claudia Kubatzki, Gary Rollefson, Henrieta Todorova, and Tjeerd van Andel 2006 Climate Forcing Due to the 8200 cal yr BP Event Observed at Early Neolithic Sites in the Eastern Mediterranean. Quaternary Research 66:401-420.
Winterhalder, Bruce, and Eric Alden Smith 2000 Analyzing Adaptive Strategies: Human Behavioral Ecology at Twenty-Five. Evolutionary Anthropology 9(2):51-72.
Zagorchev, Ivan 2007 Late Cenozoic Development of the Strouma and Mesta Fluviolacustrine Systems, SW Bulgaria and Northern Greece. Quaternary Science Reviews 26:2783-2800.
Zohary, D. 1996 The Mode of Domestication of the Founder Crops of Southwest Asian Agriculture. In The Origins and Spread of Agriculture and Pastoralism in Eurasia. edited by D. R. Harris. Pp. 142-158. London: University College London Press