Human behavioural ecology and Pacific archaeology

Archaeology in Oceania, Vol. 00 (2016): 1–12 DOI: 10.1002/arco.5124 Human behavioural ecology and Pacific archaeology ROBERT J. DINAPOLI and ALEX E. MORRISON RJD: University of Oregon; AEM: International Archaeological Research Institute and University of Auckland ABSTRACT The diverse islands of Oceania are ideal locations for the study of human ecology. Here, we argue that human behavioural ecology (HBE) provides a useful theoretical framework to approach a range of topics in Pacific prehistory, including, but not limited to, subsistence, territoriality, and monumentality. We further stress that the strength of this approach lies in the use of models as heuristic devices, and that HBE is not mutually exclusive from other explanatory frameworks, but complements larger research agendas in Pacific archaeology. Keywords: costly signalling, human behavioural ecology, monumental architecture, subsistence, territoriality RÉSUMÉ Les diverses ı̂les de l’Océanie sont des endroits parfaits pour étudier l’écologie humaine. Ici, nous soutenons que l’écologie comportementale humaine (HBE en anglais) fournit un cadre théorique utile pour aborder un ensemble de sujets dans la préhistoire du Pacifique, y compris, mais sans s’y limiter, la subsistance, la territorialité et la monumentalité. Nous soulignons en outre que la force de cette approche réside dans l’utilisation de modèles en tant que méthodes heuristiques, et que l’HBE n’est pas mutuellement exclusifs d’autres cadres explicatifs, mais complémentaire de plus grandes programmes de recherche dans l’archéologie du Pacifique. Mots-clés: signaux coûteux, écologie comportementale humaine, architecture monumentale, subsistance, territorialité Correspondence: Robert J. DiNapoli, Department of Anthropology, University of Oregon, 308 Condon Hall, 1218 University of Oregon, Eugene, OR 97403, USA. Email: rdinapol@uoregon.edu INTRODUCTION The Pacific islands (Figure 1) are ideal locations for the study of human ecology and evolution. Pacific Islands are characterised by geological, ecological, and climatic variability, ranging from coral atolls to volcanic and continental high islands, and span a range of latitudes from the tropics to the sub-Antarctic. This environmental variability is paralleled by a high degree of diversity in Oceanic cultures, which vary greatly in terms of subsistence practices, settlement patterns, and social organisation. Part of this cultural variability is a result of adaptation to diverse ecological conditions and, consequently, one component of explaining this diversity involves evaluating the potential influence of ecology on cultural differences. Here, we propose that human behavioural ecology (HBE) is a useful and complementary theoretical framework for exploring various questions regarding Pacific prehistory. While the approach makes use of relatively simple models, its strength lies in the development of Disclosure Statement: We declare no conflicts of interest.  C 2016 Oceania Publications precise and testable predictions about the archaeological record. Our intent here is to argue that HBE is exceptionally well suited to addressing particular kinds of questions about the archaeological record, specifically those concerning human adaptations to various socioecological contexts. In addition, an HBE approach is often not at odds or mutually exclusive from other explanatory frameworks, but is complementary to multiple approaches by providing evolutionary-scale explanations (Mayr 1993; Smith 2013). In the following sections, we briefly introduce the framework of HBE and then discuss its potential for exploring a range of issues regarding Pacific prehistory; specifically, subsistence change, territoriality, and monumental architecture. Rather than provide a comprehensive review, for each of these topics we briefly introduce a relevant HBE model and practical application. HUMAN BEHAVIOURAL ECOLOGY HBE is the study of human behavioural adaptation to environmental constraints (Smith & Winterhalder 1992). 2 Figure 1. Human behavioural ecology and Pacific archaeology The Pacific Islands, with areas mentioned in the text. HBE assumes that natural selection has shaped human decision-making to have a high degree of phenotypic plasticity, allowing individuals to respond to environmental pressures in fitness-enhancing ways (Winterhalder & Smith 1992). HBE attempts to explain a wide variety of human behaviours thought to be shaped by selection, ranging from foraging and agriculture (e.g. Kaplan & Hill 1992; Kennett & Winterhalder 2006), mobility and habitat selection (e.g. Cashdan 1992; Kennett et al. 2006b; Reeder-Myers 2014), and social interaction and communication (e.g. Bliege Bird & Smith 2005; Dyson-Hudson & Smith 1978; Gintis et al. 2001). As any given case study will involve a multitude of potential causal factors, one of the hallmarks of HBE is its attempt to reduce this complexity to its essential components through the use of simple models (Winterhalder 2002a). HBE models of adaptive behaviour are composed of a limited set of components, including a behavioural goal, a set of decision rules, a currency, and environmental constraints (Winterhalder & Smith 2000: 54). The definition of “environment” in HBE is broad and includes “everything external to an organism that impinges upon its probability of survival and reproduction” (Winterhalder & Smith 1992: 8). The generality of how the environment is conceived in HBE is necessary because models often concern behavioural adaptation to both the physical and social environment (Winterhalder & Smith 1992: 8). Questions concerning behavioural adaptation to the physical environment often employ cost–benefit analysis using optimality models (Krebs & McCleery 1984; Maynard Smith 1978), whereas those concerning the social environment often use game-theory models focused on the best strategy given the strategies of others in the population (Maynard Smith 1982). Although at its core HBE defines the environment broadly, in practice models must include environmental constraints explicitly defined as measurable parameters (Winterhalder 1980). In addition, because many HBE models deal with relatively short timescales, in archaeological applications in which the selective environmental inevitably changes, the constraints must also be expressed in terms of variable parameters. It is also important to note that the optimality assumption at the heart of these models should not be misinterpreted as a claim that all individuals behave so as to maximise their reproductive success, or that everything that exists is an adaptation (Gould & Lewontin 1979; Maynard Smith 1978). Instead, the optimality assumption is a measurement device used to assess how closely empirical data meet or deviate from model-based predictions, and deviations from optimality often lead to other interesting conclusions and avenues for hypotheses building (Shennan 2002). HBE has often been critiqued on the grounds that its models are overly simple, environmentally deterministic, and do not allow for human agency (e.g. Joseph 2000). Our opinion is that these critiques are misguided for several reasons. First, the strategy of reducing complex phenomena to their essential components through the use of simple models is one of the main strengths of scientific explanation  C 2016 Oceania Publications 3 Archaeology in Oceania (Richerson & Boyd 1987; Winterhalder 2002b). Overly complex models with variables and parameters for every real-world component of a case study are prone to the problem of overfitting – they explain both the phenomena of interest but also the “noise”. The result is a potential model reconstruction of the case study, but the complex model is difficult to interpret and useful only for that one example. In contrast, while the use of simple models inevitably sacrifices specificity in favour of generality, this is an explicit tactic that allows us to compare and explain a wide range of empirical phenomena (Levins 1966). Second, HBE is not environmentally deterministic, but places heavy emphasis on the important role of various environmental parameters influencing human behaviour at the population scale. Following from this, HBE does not deny human agency, but merely assumes its existence and importance in creating variability for evolutionary forces to act on (Smith 2013). In contrast to applications in the paradigm of evolutionary archaeology, HBE practitioners have focused less on how analytical units are formed and the association between measurement units and theoretically derived hypotheses. Some of this discrepancy may in part be the result of the close connection early archaeological applications of evolutionary ecology shared with foraging theory applications in ecology. Units used in foraging theory are often based on the classification of species according to different energetic return rates, usually approximated through prey body size in archaeological studies. However, researchers have also created analytical units based on other criteria used to define membership into a given class. For example, when assessing the impact of technological changes on foraging efficiency, it is not uncommon for analysts to classify prey taxa according to preferred capture technology (e.g. Allen 1992). Moreover, HBE studies that examine the effects of environmental variables on foraging patterns may organise prey taxa into classes based on habitats hypothesised to have been susceptible to some external change (e.g. Morrison & Cochrane 2008). In this sense, taxa are placed into classes that are purposively generated to track a relevant pattern in the context of a predefined research question. A substantial amount of attention has also been placed on understanding how the data requirements in archaeological applications of HBE differ from non-archaeological applications. This issue has been particularly prevalent when discussing studies of human impacts on prey populations, which are generally signified by declining foraging efficiency as measured by a change in the ratio of small-bodied to large-bodied prey (or some other criteria) in the archaeological record. However, researchers have also noted that a range of processes can result in similar archaeological patterns, including taphonomy, sampling biases, and behavioural processes, which may lead to identical archaeological phenomena. A number of models have been developed to address the issue of epiphenomena (Morrison & Allen 2015). In this regard, HBE applications are no different than other theoretical frameworks applied  C 2016 Oceania Publications to the archaeological record that incorporate principles generated from the observations of living organisms, and a variety of approaches have been developed to deal with the particular dilemmas presented by the formation of the archaeological record (e.g. Schiffer 1983). Below, we discuss previous and potential applications of HBE in Pacific archaeology with reference to three regionally important topics: subsistence change, territoriality, and monumentality. These three topics are by no means exhaustive of the potential applications, but are chosen because each lends itself to formal analysis using well-established classes of models, such as those based on foraging theory, economic defendability, and costly signalling. SUBSISTENCE As migrating populations colonised new islands, they often had to adjust their subsistence strategies in innovative ways. For example, new arrivals to New Zealand’s South Island quickly adjusted their subsistence strategies from one based on tropical Polynesian cultivars to those more suitable to a temperate climate. Similarly, the first people to arrive on Rapa Nui would have encountered marginal marine and terrestrial habitats, necessitating a heavier focus on dryland cultivation of drought resistant crops. In contrast, the diverse ecology of the Hawaiian Archipelago presented a patchwork of areas with varying subsistence opportunities and constraints (e.g. Ladefoged et al. 2009). In addition to differences in the resource availability on islands, subsistence patterns are also mediated by climate variability (e.g. Allen 2004) and anthropogenically induced resource depression (e.g. Allen 2012; Butler 2001; Nagaoka 2002). Subsistence is particularly amenable to foraging theory (FT) models, one component of HBE. FT has been used in archaeological studies to address subsistence patterns since the 1970s (e.g. Jochim 1976). These models are applicable across a diversity of regions and subsistence regimes, including domesticates and wild food sources. FT models generally assume that subsistence decisions have been shaped to maximise some element of inclusive fitness, either by increasing energy acquisition, optimising time allocation, or minimising risk. The most common currency used in foraging models is energy gained per unit of time foraging, often approximated archaeologically by prey body-size (Broughton et al. 2011). However, when prey are mass-harvested, such as during the collection of rocky shoreline molluscs, the energetic unit will need to be adjusted to represent the cluster of items collected instead of individual prey (Madsen & Schmitt 1998). Technological innovations can also decrease handling time and increase extraction rate, a situation assessable through analyses of covariation between artefact attributes and faunal patterns (discussed below). The prey-choice model, one of several commonly used FT models, predicts that prey will be included in the diet only if the post-encounter net energetic return is greater than 4 the average return-rate of all higher-ranked items already in the diet. If the encounter-rate of high-ranked taxa does not change and technological innovations that affect processing and harvest-rate do not occur, foraging efficiency should remain stable. When higher-ranked items decrease in abundance, foragers will choose a wider array of lowerranked items, resulting in lower overall foraging efficiency. Archaeologically, this would be indicated by a widening of the diet breadth to incorporate less profitable (i.e. smaller-bodied) prey, an increase in taxonomic diversity and an increase in the incorporation of younger individual prey. In addition to the prey-choice model, the patch-choice model is often applied in ecological contexts where prey form aggregated spatial distributions and all prey in the diet are not searched for simultaneously (Charnov & Orians 1973). Instead of focusing on which prey foragers should pursue, the patch-choice model deals with how individuals should allocate time spent foraging in different habitats. For example, as prey abundance decreases in a heavily exploited habitat to the point at which it equals in rank to other available patches (accounting for travel time) the model predicts migration into new habitats (Charnov 1976: 129). The patch-choice model is particularly important in contexts where multiple ecotones, such as offshore marine areas, nearshore environments, and inland hunting grounds, are readily exploited (e.g. Nagaoka 2002). Prey population declines and variability in prey use are important topics in HBE studies (e.g. Broughton 1994). If the encounter-rate of high-ranked prey decreases to the point where lower-ranked taxa are incorporated into the diet, foraging efficiency declines because the energetic return-rate decreases. This scenario is termed resource depression (Charnov et al. 1976), and is potentially caused by a number of factors. Charnov et al. (1976) identify three different types of resource depression, although the processes responsible for each may be difficult to assess empirically with archaeological data. First, exploitation resource depression occurs through predation, which leads foragers to encounter prey less often as increasing members of the population are removed. Second, behavioural resource depression results from prey life-history characteristics that influence encounter and capture-rates, including prey mobility, flocking strategies and overall behavioural responses to the presence of predators. Finally, microhabitat resource depression refers to locational shifts in prey as they respond to changes in habitat or hunting pressure. Microhabitat resource depression and behavioural resource depression do not require an absolute decrease in prey population numbers but, rather, a shift in the encounter-rate of prey as they move into locations that are more difficult for predators to access. It is important to recognise that changes in forging efficiency are not solely the result of human-predation but a multitude of processes that may influence prey encounter-rate. Moreover, the strengths of FT and optimisation models, in general, do not rest on the model assumptions always being met. Instead, optimisation models provide tools for measuring the degree to which Human behavioural ecology and Pacific archaeology individuals were behaving optimally (Orzack & Sober 1994: 378-9) and empirical deviations from the model predications, which are common, lead to the construction of new model components and more nuanced explanations. For example, although a plethora of archaeological studies using HBE principles document human-induced resource depression, it is important to note that many of the most productive studies are produced when the empirical results do not clearly fit the expectations of the model predictions. For example, Giovas et al. (2013) demonstrate that certain species of invertebrates in the Lesser Antilles, Caribbean Islands, show no clear signs of resource depression despite nearly 1500 years of predation (for a similar study, see also Giovas 2016). Additionally, Morrison and Addison (2008, 2009) document approximately 1500 years of stability in fish and invertebrate remains at the Fatu-ma-futi Site in American Sāmoa. Formal models incorporating prey life-history traits (e.g. age and size at reproductive maturity, clutch size, and reproductive rate) with HBE principals help to explain why specific prey are resilient to human predation while others more susceptible (e.g. Morrison & Allen 2015; Whitaker & Byrd 2014). Combining life-history theory and HBE leads to fruitful insights regarding the extinction of large avifauna during the initial colonisation of many island ecosystems. Perhaps the best known example comes from the rapid extinction of the New Zealand moa (Aves: Dinornithiformes), within 150–200 years of colonisation by Polynesians (Allentoft et al. 2014; Perry et al. 2014). As a result of their large size, lack of fleeing capabilities, and overall abundance, moa would have been an attractive prey for early settlers of New Zealand. Indeed, the archaeological record attests to the overwhelming importance of moa and other large prey species like seals and sea lions, during the early period of human prehistory (Anderson & Smith 1996; Nagaoka 2002). Focus on moa and other large-bodied prey makes sense in light of the high caloric return rate that these animals would have offered foragers. However, moa, like other large flightless birds, were also particularly susceptible to extinction due to a number of intrinsic biological characteristics often found in long-lived birds (slow growth rate, small clutch size, and older age at reproductive maturity) (Holdaway & Jacomb 2000). When combined with their attractiveness to human predators, these life-history characteristics made the moa particularly susceptible to human predation and the associated effects of habitat modifications caused by human activities. Application of foraging theory in Pacific Island archaeology Many applications of FT in Pacific Island archaeological contexts focus on marine resource use (e.g. Anderson 1981; Allen 1992, 2012; Butler 2001; Morrison & Hunt 2007). In general, these studies document human impacts on wild prey, especially in the context of colonisation of new island ecosystems; however, there are numerous examples of prey resilience to predation and overall stability in subsistence trends (e.g. Giovas et al. 2016; Morrison & Addison 2008,  C 2016 Oceania Publications 5 Archaeology in Oceania 2009). Here, we briefly discuss a number of compelling case studies. In an early example from Palliser Bay, New Zealand, Anderson (1981) applied an analytical model based on FT. During the 600-year Palliser Bay sequence, shellfish assemblages show evidence of change in exploitation from larger- to smaller-bodied taxa, and size reduction in commonly exploited molluscs is also evident. These results are consistent with expectations of the prey-choice model and exploitation resource depression, although other cultural and environmental factors cannot be ruled out. At Harataonga Beach, also in New Zealand, Allen (2012) used both prey- and patch-choice models to explain a shift from large mollusc taxa, such as Cookia sulcata, first to intermediate size species such as Turbo smaragdus, and then finally to the small nerite Nerita atramentosa. Similar to Palliser Bay, these patterns are consistent with the expectations derived from FT and may indicate exploitation resource depression or other cultural factors associated with forager mobility. Pacific Island archaeological studies that focus on fish assemblages (e.g. Butler 2001; Morrison & Addison 2009; Nagaoka 2001, 2002) have also incorporated foraging theory models into formal analyses. Nagaoka (2001, 2002) applied a combination of prey- and patch-choice models to both terrestrial and marine vertebrate assemblages from the Shag River Mouth site, New Zealand. The results demonstrate that early in the archaeological sequence, humans relied heavily upon large-bodied prey such as moa and pinnipeds and that through time within both the inland and coastal habitats, foraging efficiency dropped as these large-bodied taxa declined. In addition to measurable changes in taxa acquired from within the inland and coastal habitats, as overall foraging efficiency declined, the offshore habitat became more intensively used. As a result of the close relationship between technological change, subsistence strategies, and prey population dynamics, models that are useful for studying subsistence patterns are analytically powerful when paired with formal analysis of functional technological traits (e.g. Bettinger et al. 2006; Surovell 2009). In an innovative analysis, Allen (1992) used a HBE framework to assess how changes in fishhook raw material may have influenced variation in fish catch composition. Specifically, on Aituaki, and elsewhere in the Southern Cook Islands, pearl shell (Pinctada margaritifera) fishhooks decline through time and are ultimately replaced by hooks made of Turbo shell (Turbinidae) (Allen 1992; Walter 1989). Allen notes a positive correlation between the decline of pearl shell fishhooks and a decrease in Lutjanidae (snapper) in the fish assemblage and suggests that there is probably a functional relationship between the two. Moreover, fishhooks in general decline through time on Aituaki and may signify a movement away from angling towards netting and/or spearing. Studies of fishhook design characteristics (Allen 1996) highlight the importance that technological innovation and functional variation have on prey choice, subsistence change, and patterns of faunal use in the  C 2016 Oceania Publications archaeological record. These studies are important because they illustrate the close relationship between harvesting technology, catch composition, and changes in foraging efficiency. A number of researchers have also pointed out that life-history characteristics, such as reproductive rate, colonial structure, and age at reproductive maturity, as well as other ecological factors, influence prey resilience and susceptibility to resource depression, and should therefore be considered when applying HBE models (e.g. Giovas et al. 2016; Morrison & Allen 2015). In short, the use of fairly simple analytical models has led to remarkable sophistication and a more nuanced understanding of complex ecological contexts and archaeological patterns. CONFLICT AND TERRITORIALITY The emergence of conflict and territoriality is a common theme in the prehistory of the Pacific and is considered an important prerequisite for the evolution of social complexity (e.g. Kaplan et al. 2009; Kirch 1984; Mattison et al. 2016). Here, territoriality is defined as any behaviour that deters others from accessing a given territory; that is, an area of land for which one controls exclusive access (Dyson-Hudson & Smith 1978; Fretwell 1972). Archaeologically, territoriality is often exhibited in the Pacific by land divisions and defensive features such as fortifications (e.g. Field 2005; Kennett et al. 2006b; Ladefoged & Graves 2006). Further signs of conflict may occur in the form of skeletal trauma or weapons (Field 2008). This archaeological evidence of physical conflict and territoriality is common throughout the Pacific and is often argued to correlate with periods of regional climatic instability (e.g. Field & Lape 2010). However, high levels of physical conflict and territoriality do not occur everywhere. For example, fortifications, weapons, and lethal conflict are conspicuously absent on Rapa Nui (Field & Lape 2010; Lipo et al. 2016; Owsley et al. 2016). This heterogeneity in the occurrence of territoriality therefore requires an explanation, and the economic defendability model (EDM) is particularly well suited to address this issue (Dyson-Hudson & Smith 1978; Field 2008). A resource is said to be economically defendable when the benefits of maintaining exclusive access to a territory outweigh the costs of defence (Brown 1964). Some costs of territoriality include energetic investment in defence, potential injury, land maintenance, and the opportunity costs of relying on a restricted area, whereas the benefits of territorial behaviour stem from exclusive control over resources (Cashdan 1992; Dyson-Hudson & Smith 1978: 24). The EDM posits a close link between these costs and benefits and the structure of resources in a given environment, and demography is also a crucial component because competition is only expected to occur when resource abundance is restricted relative to population density (Boone 1992; Field 2008). The EDM yields a number of predictions about the intensity of territoriality expected under different environmental parameters (see 6 Human behavioural ecology and Pacific archaeology Table 1. The effect of different resource structures on economic defendability, resource utilisation, and degree of mobility predicted by the EDM. Table from Dyson-Hudson and Smith (1978). Resource structure Economic defendability Resource utilisation Degree of mobility Unpredictable and dense Unpredictable and scarce Predictable and dense Predictable and scarce Low High Low Information sharing Dispersion High Territoriality Low Fairly low Home ranges Low-tomedium Very high Table 1). For example, in environments where resources are of lower quality, dispersed, or unpredictable, economic defendability is predicted to be low (Dyson-Hudson & Smith 1978). This is because the uncertain payoff from dispersed and unpredictable resources means that the costs of territory defence will be quite high, and we should expect a lack of territoriality and high levels of cooperation and/or mobility (Dyson-Hudson & Smith 1978). However, high levels of competition and territoriality are predicted when resources are dense and predictable (Dyson-Hudson & Smith 1978). In this kind of environment, the high economic defendability of dense and predictable resources allows for low-cost defence of small areas and high energetic benefits from constant high-quality resources (Davies & Houston 1984; Dyson-Hudson and Smith 1978: 25). In addition, exclusive access to dense and predictable resources not only provides benefits to the individuals performing defence, but also to their kin and offspring in the form of intergenerational resource transfers (Mattison et al. 2016). It is in these kinds of environments we should expect to see evidence for physical conflict, fortifications, and territorial boundary markers. The EDM is useful because it can help us understand varying degrees of competition, and also why territoriality is not likely to occur in certain times and places. In addition, the model predictions can be readily tested using palaeoenvironmental and archaeological data. Applications of the economic defendability model in Pacific Island archaeology Field’s (1998, 2004, 2005) investigations of the rise of conflict and territoriality in the Sigatoka Valley on Viti Levu, Fiji provide one of the most comprehensive applications of the EDM in Pacific archaeology. The Sigatoka Valley is an area of dense prehistoric settlements, the majority of which are heavily fortified by walls and ring-ditches or located in naturally defensive locations on hilltops (Field 1998, 2004). In addition to this widespread archaeological evidence for territoriality, ethnohistorical data indicate high levels of inter-group conflict and a dense patchwork of named territories throughout the valley (Field 2005). Using a variety of geospatial techniques, Field (1998, 2004, 2005) quantifies three zones of resource density and predictability across the valley. As predicted by the EDM, the greatest number of fortifications occur early in areas with the highest potential agricultural yields (Zone 1). However, Field’s (2004) palaeoclimate modelling suggests that during the Little Climatic Optimum/Little Ice Age (LIA/LCO) transition (c.700–500 BP) resource quality, and hence economic defendability, in Zone 1 would drop significantly. In this scenario, the EDM predicts a switch to non-territorial behavioural strategies or increased levels of mobility. Interestingly, this is precisely what the Sigatoka Valley evidence indicates – during the LCO/LIA transition, there is evidence for resettlement and fortification construction in the adjacent Zones 2 and 3, which have somewhat lower-quality resources but higher levels of temporal predictability (Field 2004). With climatic stabilisation following the LCO/LIA, there is an increase in the construction of fortifications in Zone 1 around 500 BP (Field 2004). This later period of increased conflict and territoriality is explicable in terms of the EDM (i.e. a return to dense and predictable resources) and is probably reflective of the contact-era settlement system (Field 2005). In sum, evidence from the Sigatoka Valley is a prime example of how the varying spatiotemporal patterns of fortification construction are usefully explored using the EDM. Field’s use of the EDM provides a prime example of how HBE can help us understand patterns and processes of territoriality (see also Anderson & Kennett 2012; Kennett et al. 2006b; Ladefoged 1995), and also highlights the potential for using temporally static HBE models in an iterative fashion to produce dynamic explanations. In a vacuum, the EDM merely predicts when we should expect the appearance of territoriality. However, following from the assumptions of the model, if those environmental conditions persist, or change, then the behavioural response is predicted to change accordingly. This model-based approach could be usefully applied both to other fortified islands, such as those of Palau (Liston 2009), Sāmoa (Best 1993) and New Zealand (Walton 2001), and those lacking evidence for physical conflict and territoriality. For example, the prehistory of Rapa Iti in the Austral Islands is characterised by a high degree of conflict and territoriality, which Kennett and colleagues (Anderson & Kennett 2012; Kennett et al. 2006b) argue is a result of its restricted land area and the high economic defendability of its irrigated agricultural systems. In contrast, lack of evidence of fortifications on Rapa Nui probably results from its very different resource potential, which is in general marginal and unpredictable (Louwagie et al. 2006). In these cases, explanatory models such as the EDM can be used to compare and contrast varying degrees of territoriality in the region (Field 2008). COSTLY SIGNALLING A pervasive characteristic of the archaeological record in Oceania is the large-scale investment in activities requiring  C 2016 Oceania Publications Archaeology in Oceania high energy expenditure but lacking clear utilitarian function. These kinds of “cultural elaboration” (Graves & Ladefoged 1995; Hunt & Lipo 2001) occur in the form of elaborate prestige goods, such as finely decorated Lapita ceramics, and monumental earth and stoneworks found throughout Oceania. Explanations for these phenomena have generally focused on the legitimisation of power through religious means (e.g. Kirch 1990; McCoy 2014) as well as signs of sociopolitical competition and consolidation (e.g. Kolb 2006). Cultural elaboration is puzzling from an HBE perspective because it clearly involves an enormous energy investment but seemingly lacks clear returns on that investment. In other words, how do we, from an evolutionary standpoint, explain the persistence of behaviour that seems to have costs that are much greater than the benefit? Costly signalling theory (CST) proposes that some energetically expensive behaviours are adaptive in socioenvironmental contexts because they signal information about an individual’s unobservable qualities, such as reproductive fitness or potential as an alliance partner (Grafen 1990; Zahavi 1975). Numerous examples of costly signalling are found in the anthropological literature, such as monumental architecture (e.g. Glatz & Plourde 2011; Neiman 1997), elaborate prestige goods (Plourde 2008; Plourde & Stanish 2006), feasting displays (Bliege Bird & Smith 2005) and dangerous and time-consuming hunting (Smith et al. 2003). The display of these costly signals is hypothesised to benefit both signaller and receiver, because each potentially gets a higher payoff from the signalling strategy than assessing unobservable qualities in other, more costly, ways, such as through physical conflict. Costly signalling provides a benefit to the signaller by increasing the probability that they will be chosen as a mate or a political ally, or deferred to as a dominant in a competitive bout (McAndrew 2002: 3). For example, two individuals competing over a resource patch would both benefit if the outcome of the competition was apparent prior to the commencement of actual fighting. The signal also serves an advantage to recipients of the advertisement, because they can adjust their own strategy according to this new information, since it is beneficial for the recipient to avoid engaging in a fight if they will surely loose. In addition to its role in competitive contexts, costly signalling has also been shown to be a powerful force in maintaining cooperation within groups (Gintis et al. 2001). Importantly, for a signal to qualify as “costly” and provide a selective benefit to both sender and receiver, it has to honestly represent the underlying trait being advertised; otherwise, as receivers learn the deception of the display, through time the signal will be ignored and no benefit to the sender will ensue (Grafen 1990). Therefore, production of the signal must incur a cost to the sender that is directly proportional to the magnitude of the display such that it is not possible to cheat. The relationship between display magnitude and subsequent cost can be met by low-quality signallers either paying higher marginal costs or reaping lower marginal benefits (Smith & Bliege Bird 2005: 116).  C 2016 Oceania Publications 7 Under these conditions, the cost of the signal ensures its honesty (Grafen 1990; Maynard Smith & Harper 2003). Although the basis for CST was originally discussed over a century ago by Veblen (1899), and later presented in the context of evolutionary biology by Zahavi (1975), economic and evolutionary models were not formalised until the 1990s (Grafen 1990; Zahavi & Zahavi 1999) and it has only recently seen application in archaeology (e.g. Glatz & Plourde 2011; Neiman 1997). Specific applications of CST to the archaeological record have generally focused on monumental architecture and its role in signalling political power. Here, we briefly discuss a single compelling case study. In a study of monumental architecture in Late Bronze age Anatolia, Glatz and Plourde (2011) argue that monuments represent a medium through which political competition and territoriality were moderated (see also Neiman 1997). They use CST to generate predictions about the spatial distribution of monuments, specifically that: (1) monument placement, size, and quality indicate the geographical scale of political interaction and overall degree of investment in signalling; (2) monuments located on the outskirts of polity centres designate the locations of politically contested spaces; and (3) fluctuation in the scale, location, size, and quality of signals reflects underlying transformations in the political landscape (Glatz & Plourde 2011: 38). In situations where one polity is visibly much stronger than another, the group of lesser strength is unlikely to challenge the dominant group, which may continue to grow uninterrupted. However, when groups have similar resource holding potential, signalling may be intense and lead to the avoidance of costly conflicts. Here, investment in monumental architecture helps to resolve potential conflicts with fewer costs than physical altercations. In the absence of advertisement, an accurate assessment of fighting strength would be difficult and any knowledge about competitive strength that can be acquired beforehand valuable (Glatz & Plourde 2011: 37). The prevalence of monuments in the region throughout the thirteenth and fourteenth centuries points to a political context that was probably unstable and required constant negotiation. Glatz and Plourde’s (2011) case study provides an interesting example of how CST can be applied to the explanation of the rise of monumentality in other regions, such as Oceania. Potential applications of costly signalling theory in Pacific Island archaeology The application of CST to the investigation of many aspects of the archaeological record of Pacific Islands, such as the persistence of monumental architecture in Eastern Polynesia (Figures 2 and 3) and the elaborately decorated ceramics of the Lapita expansion, is particularly promising, although thus far no formal applications have been applied in the region. Empirical evidence from many areas such as Tonga (e.g. Freeland et al. 2016), Hawai‘i (Kolb 1994, 2006; Kirch & Sharp 2005) and Rapa Nui (Hunt & Lipo 2011; Martinsson-Wallin 1994) indicate that investment in 8 Human behavioural ecology and Pacific archaeology Figure 2. Pu‘uoina Heiau, Kaloko-Honokōhau, Hawai‘i. Figure 3. Ahu Tongariki, Rapa Nui. monumental architecture was indeed substantial. Working with LiDAR data from Tongatapu, Tonga, Freeland et al. (2016) document approximately 10000 mounds on the island, some of which are sizable (>10 m high) and indicative of chiefly residences. At Pi‘ilanihale Heiau on Maui Island, Hawai‘i, Kolb (1994) estimates that it took 128155 labour days to complete the temple’s four building phases. Finally, the small island of Rapa Nui houses over 200 monumental ahu structures (Martinsson-Wallin 1994), many of which are built of extremely fine-crafted and wellfitting massive basalt walls. Moreover, there are nearly 1000 stone statues, the largest of which weighs approximately 74 metric tons and stands over 10 m tall (Lipo et al. 2013). Given the amount of effort required to produce such megaliths, these activities would have been extremely costly and certainly would have signalled an honest advertisement of the abilities of the community members they represented. In the case of Polynesian monumental architecture, signalling through the construction of monuments would have transmitted a reliable message about the political and militaristic power, potential alliance partners, and resource holding potential in contexts where this information would otherwise be difficult and potentially costly to acquire (Gintis et al. 2001: 4). In risky, uncertain and highly variable environmental contexts, such as Rapa Nui, we might expect signalling through monumental architecture to help individuals assess which social groups are likely to make strong alliance partners, as well as to evaluate the outcome of potentially aggressive interactions (Morrison 2012). Roscoe (2009) suggests that in small-scale social groups, ritualised fighting, like monumental architecture, provides a low-cost means for individuals to assess the competitive capabilities of potential political rivals without sustaining serious injuries as a result of an actual physical altercation. The selective role of signals would have been particularly important in small-scale societies, like Rapa Nui, that perhaps lacked the centralised political control necessary to mediate potential conflicts. Hunt and Lipo (2011) have also suggested that costly signalling may help to explain the temporal and spatial distribution of monumental architecture on Rapa Nui, offering a fruitful avenue for future research. Indeed, initial steps have recently been taken to quantify the spatiotemporal patterns of energy investment in Rapa Nui monuments (e.g. Shepardson 2006). The empirical expectation of such a model would require: (1) measurement of differences in resource holding potential, perhaps by modelling spatial variation in agriculturally productive land or some other critical resource; and (2) a comparison of investment in monumental architecture across the same region. Settlement pattern studies that document community structure and the location of settlement across space will also be critical for assessing how monuments were used to negotiate territorial spaces. DISCUSSION AND CONCLUSIONS In the preceding sections, we have explicated three topics – subsistence, territoriality, and monumental architecture – where HBE models can help provide evolutionary-scale and complementary explanations of Pacific prehistory. However, this theoretical approach is by no means restricted  C 2016 Oceania Publications 9 Archaeology in Oceania to these topics. For instance, CST is also applicable to the development and display of elaborate prestige goods, such as Lapita ceramics, which potentially signal individuals’ skill and other traits (Henrich & Gil-White 2001; Plourde 2008: 9). Indeed, several scholars suggest that Lapita ceramics may have operated as a form of prestige good (e.g. Chiu 2005). Summerhayes and Allen (2007) explicitly make note of the potential of CST for understanding how the production of Lapita pottery aided settlers colonising new environments. In addition, the implications of HBE models can be useful for examining larger substantive issues in Pacific archaeology, ranging from optimal and risk-reducing agricultural strategies (e.g. Allen 2004), settlement patterns (Crema 2014; Morrison 2012; Rieth et al. 2008) to the timing and nature of island colonisation (e.g. Kennett et al. 2006a; Reeder-Myers 2014). For example, habitat selection models such as the ideal-free and despotic distribution (see Fretwell & Lucas 1969) are well suited to exploring issues ranging from colonisation and mobility (e.g. Giovas & Fitzpatrick 2014; Kennett et al. 2006a; O’Connell & Allen 2012; Winterhalder et al. 2010) to the emergence of social complexity (e.g. Bell & Winterhalder 2014; Boone 1992; Kennett et al. 2009). The application of HBE to these topics is promising because the models often provide very specific and testable predications about the archaeological record. HBE models are also not context-specific, so they can easily be employed to address similar topics in different island regions, providing comparative explanations for patterns of evolutionary divergence. One of the core strengths of the HBE approach is its heuristic use of simple models. The heuristic nature of HBE models means that archaeologists can generate testable hypotheses for multiple models, and when one does not prove useful, it can be discarded it in favour of another. For example, using the prey-choice model, we can derive empirically testable hypotheses that can be evaluated using faunal data. However, a particular model may not work well in all cases, such as when additional factors, like travel time, are relevant and we may want to incorporate components of other models (such as central-place foraging). The crucial point is that none of these models is “true” or “correct”, but that they are useful as measurement devices. Importantly, HBE-based explanations of the archaeological record should not be seen as mutually exclusive from other theoretical paradigms. The reason for this is that accounts rooted in evolutionary causation provide different and complementary kinds of historical explanations (Mayr 1993). For example, approaches to questions about chiefly competition and the emergence of social inequality based on political economy (e.g. Earle & Spriggs 2015; Kirch 2010) can be complemented by formal analysis using HBE concepts of economic defendability, despotism, and patron–client relationships (e.g. Boone 1992; Mattison et al. 2016; Smith & Choi 2007; Smith et al. 2016; Summers 2005). Such an approach could provide specific and comparable predictions for why components of social complexity are found in particular times and places. Similarly, agency-based accounts of how  C 2016 Oceania Publications elites, by striving for power and prestige, facilitate the construction of monumental architecture in particular social and ritual contexts (e.g. Kahn & Kirch 2014; Kolb 2006) work at a different analytical scale than HBE explanations, such as CST, which can help provide explanations for why monument construction occurs at all (Kuhn 2004: 566; Smith 2013). Not only are these different scales of analysis not at odds, but together they can provide more complete and complementary accounts of the past. ACKNOWLEDGEMENTS We thank Peter White and Peter Sheppard for inviting us to guest edit and contribute to this special issue of Archaeology in Oceania, Brian Lane for assistance translating the abstract into French, and Carl Lipo for assistance in creating Figure 1. We also thank Michael Graves and an anonymous reviewer for helpful comments that greatly improved the manuscript. REFERENCES Allen, M.S. 1992. 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