Abstract and Keywords
Stratigraphic excavation is perhaps the defining technique of archaeological research, since it is this approach that provides the necessary contextual information for all other forms of archaeological sampling. Rightly perceived as intensive in terms of labour, time, and resources, excavation seems at odds with the aims of developmental interventions that are often under pressure to produce rapid and sustainable solutions to immediate and ongoing environmental and human crises. Drawing on research in eastern Africa, this chapter will argue that some questions of relevance to developmental and conservationist debates can nevertheless only be answered through detailed stratigraphic data, and that these data are essential in order to construct models of landscape change and to assess the sustainability and resilience of these landscapes.
The 12 chapters in this section present a very broad range of methodologies illustrated by a diverse collection of case studies, with these case studies ranging in date from the Neolithic (e.g. the chapters by Barton and French) to communities in the present (e.g. the chapter by Balée and Nolan). Although the vast majority of the authors are archaeologists, the methodologies outlined and discussed are not restricted to what we might think of as quintessentially archaeological techniques: no chapters deal with the study of artefacts (though French, Heckbert et al., and others note their value as part of broader inter- and multidisciplinary studies), only one chapter focuses exclusively on stratigraphic excavation (Stump), and only one concentrates entirely on the study of animal remains (Lyman), albeit with a focus on what the data can tell us about modern wildlife conservation. Instead, many of the chapters emphasize the value of historical sources, including documentary evidence, oral history, and pictorial data (Årlin et al., Coutu, Ford and Clarke, French, Hicks et al., Lindholm, and Sulas), and most stress the need to cross-reference as many proxies of human and ecological change as possible (particularly Coutu, French, Hicks et al., Heckbert et al., Lindholm, and Sulas). In part this reflects the important recognition that change occurs through interactions between human, environmental, and climatic factors. However, there is a second important reason for this emphasis on interdisciplinarity, with several authors arguing that archaeological evidence will never be able to address complex issues of human–environment interactions alone, because archaeological data are generally too fragmentary and too subject to biases of preservation (in particular Barton, French, Lyman; see also Minnis, Chapter 2), and because only descriptive records can provide culturally-specific information on the motivations of human individuals or communities (particularly Årlin et al., Lindholm, Lyman, Stump, and Sulas).
This recognition that the archaeological record is always incomplete leads different authors to very different conclusions, however. Lyman, for example, notes that those he terms ‘neozoologists’ (i.e. those who study extant species) have been dismissive and sometimes actively critical of the value of palaeozoology, primarily on the grounds that palaeo-data are incomplete. Lyman counters this conclusion, demonstrating that (p. 134) although palaeozoology cannot provide accurate figures for the number of individuals in past populations, it can accurately reconstruct relative abundance, and has the advantage that it can see adaptive responses of particular species (for example changes in diet through isotope analyses—see also Coutu), and can see both decreases and increases in biodiversity, since unlike neozoology, palaeozoology can record species extinction and speciation. Lyman thus concludes that conservation efforts are improved by combining neozoological and palaeozoological data; a conclusion echoed by Coutu, who uses isotope analyses from historic African elephants to demonstrate how elephant behaviour differed before their movements were restricted within conservation areas, and argues that an understanding of this behaviour could help design wildlife corridors.
Barton, in contrast, draws a very different conclusion from the recognition that archaeological data are never complete and rarely unambiguous, and proposes what many will see as a radical conceptual change: rather than use archaeological data to help reconstruct the past, it should be used to validate hypotheses about the causes and consequences of change. In other words, rather than use archaeological data to create a model of, for example, historic landscape change, models should hypothesize how two or more factors will interact (e.g. that increasing population densities will lead to increased soil erosion) and then compare the results of simulations with the archaeological record. The advantages of doing so, Barton argues, is that hypotheses are not restricted to those that arise from the (incomplete) archaeological record, and models can simulate processes that take centuries to occur and which therefore cannot be compared with (or validated by) modern observational data that typically spans a few decades at most. Barton’s approach thus appears to be the opposite of that presented by French, who argues that computer simulations can act as aids to archaeological interpretations only after scenarios have been hypothesized by integrating as many data sources as possible, and where it is stressed that models ‘are only to be seen as possible explanations’. In short, Barton argues that simulated processes derived from hypothesized interactions can be tested in reference to long-term data, while French argues that the veracity of archaeological interpretations of past processes can be tested via simulations. However, since both these approaches are reliant on robust data, and both are concerned with identifying tipping points and thresholds of change that are of potential modern relevance, these distinct methodologies can be regarded as complementary rather than oppositional. Indeed, provided that care is taken to avoid circular arguments (e.g. testing models against the same data used to create them), it is possible for simulations to employ a combination of palaeo-data, observational data, and hypothesized processes in a number of ways, examples of which are also discussed by Ford and Clarke and by Heckbert et al.
A common theme is the importance of scale: not just the need to understand processes over long time frames, but also recognizing that the processes or activities occurring in one area may be impacted by processes or activities occurring elsewhere or at a different spatial scale. The most obvious example of this is how the sustainability of discrete agricultural systems can be impacted by global climate change or world-systems relations, but interactions at local scales are also significant. Stump, for (p. 135) example, shows how an agricultural system in east Africa was sustained for centuries by capturing sediments eroding off the adjacent highlands, but it is possible that erosion was itself due to unsustainable processes: a system that appears sustainable at one scale may therefore prove to be unsustainable when wider-scale factors are considered. Time scales are of course important too, since this system of capturing eroding sediments may have been sustainable for a certain time span but unsustainable thereafter, or may have been sustainable only as long as rates of erosion did not exceed rates of soil renewal. Exploring the interaction of processes that occur at different spatial scales, different temporal scales, and at different rates, thus forms a major component of many of the chapters in this section, but the various authors approach this issue in a variety of ways, and correspondingly draw different lessons. Balée and Nolan, for example, demonstrate the importance of understanding cycles of resource exploitation within a landscape via a case study in which former settlement sites remain a critical resource because their gradual reforestation is carefully managed to provide ‘indigenous orchards’ (for comparable examples see Belharte, 2011). Ford and Clarke employ archaeological data to take a far longer-term view of the very similar milpa system employed by the Late Classic Maya, and argue that this could support large populations while conserving forest resources. This perhaps contrasts with the modelled outcomes presented by Heckbert et al., who, looking at the Maya economy as a whole, see soil depletion and erosion as a common outcome of complex system processes. In doing so, however, Heckbert et al. also make the important observation (along with Barton, French, and Lyman) that systems can cross tipping points towards unsustainability long before human communities can possibly be aware of the processes at play, either because these trade-offs are occurring too slowly to be perceived, or because they are occurring at scales that are too small, too big, or too remote to be seen (see Hegmon, 2017). This recognition has clear significance for sustainability studies since it emphasizes that decisions are often made on the basis of imperfect information, and acts to counter simplistic assertions about the potential value of long-term data: demonstrating that a system has been sustained for long periods in the past does not mean that it will continue to be sustainable in the future.
Hicks et al. present a case study that they interpret as demonstrating long-term sustainability (the exploitation of wild birds and bird eggs over 1,000 years in northern Iceland), but raise the important issue of intentionality (see also Arroyo-Kalin, Chapter 6) and note that individuals might choose to ignore societal rules designed to promote the maintenance of a resource. Both of these observations lead to the same conclusion: one does not need a conscious ‘conservation ethic’ in order to conserve resources, to which might be added the problem that purely archaeological studies may find it extremely difficult to distinguish intentional conservation from mere lack of exploitation due to factors such as dietary taboos. These issues, together with the scale factors noted above, combine to prompt the calls for interdisciplinary analyses highlighted by all of these chapters. Sulas illustrates this well, noting that geoarchaeological interpretations are substantially strengthened by complementary techniques that can provide details of human decision-making, landscape perception, and vegetation change (p. 136) (see also Butzer, Chapter 7), while also noting that different data sources and techniques have different spatial and temporal resolutions.
Like Sulas, the chapters by Årlin et al. and Lindholm reinforce the pivotal point that perceptions about the past (whether they are true or not) have an enormous influence on how we perceive the present, and thus become enmeshed within modern politics, sometimes in ways that require analysis to define and unpick. The mere act of highlighting these conscious and unconscious biases or the legacies of past political decisions is itself a form of ‘usable past’ (Lindholm), and is an important aspect of any attempt to directly engage with modern communities (Årlin et al.).
Belharte, S. (2011). The ecological view: management of tree crops and the transition to vegeculture in Southeast Asia and the Pacific. In G. Barker and M. Janowski (eds), Why Cultivate? Understandings of Past and Present Adoption, Abandonment, and Commitment to Agriculture in Southeast Asia. McDonald Institute Monographs. Cambridge: McDonald Institute for Archaeological Research, 27–46.Find this resource:
Hegmon, M. (ed.) (2017). The Give and Take of Sustainability: Archaeological and Anthropological Perspectives on Tradeoffs. New York: Cambridge University Press.Find this resource: