# EEMIAN DISTRIBUTION OF NEANDERTHALS

Abstract

Aim: We hypothesize that the northern and southern edges of Neanderthals distribution during the Last Interglacial were respectively limited by low winter temperatures, and high temperatures and lack of rainfall during the summer, while high topographic diversity combined with moderate slopes favored presence at the local scale.

Location: Europe (20ºN to 70ºN, 10ºW to 70ºE).

Methods: We used Neanderthal presence, palaeoclimatic, and topographic data to calibrate a species distribution model. We analyzed variable importance at the continental scale with Randon Forest, and at the local scale with local regression and recursive partition trees.

Results: Highest habitat suitability was observed along the Mediterranean coast. Main mountain ranges and continental plains showed low habitat suitability values. Extreme seasonal temperatures and annual rainfall were the most important predictors at the continental scale, while topography defined habitat suitability at the local scale.

Main conclusions: Our results challenge the notion of Neanderthals as a central European species. Therefore, many current interpretations of Neanderthal livelihood during the Last Interglacial may not accurately represent this species preferred habitat.

Keywords: palaeo-species distribution modeling, hominins, habitat suitability, ecological niche

# Introduction

Our knowledge about Neanderthals has greatly increased over the last two decades with more than two thousand research papers published in areas as diverse as chronology (Gaudzinski-Windheuser 2014, Higham 2014), ecology (Finlayson 2007, Henry 2010), population dynamics (Sørensen 2011, Bocquet-Appel 2013), adaptive traits (Sørensen 2009, Rae 2011), diet (Henry 2010, Hardy 2011), technology, cognition and behavior (Shaw 2012, Peris 2012, Riel-Salvatore 2010), genetics (Briggs 2009, Sanchez-Quinto 2014), and their relationship with anatomically modern humans (Hortolà 2013, Sankararaman 2012). Still, we believe there is a lack of tangible information about the factors controlling the Neanderthals’ distribution. For example, Wenzel (2007) describes the distribution of Neanderthals during MIS 5e across central Europe, and briefly discusses the influence of climatic conditions and habitat features over the general occupancy pattern, but does not establish any quantitative link between presence and environment. Banks et al. (2008) analyzed the distribution of Neanderthals at the interphase of the Neanderthal/modern human transition applying palaeo species distribution models (PSDMs hereafter), assessed niche conservatism, and analyzed the importance of climatic predictors, concluding that temperature was the most important driver shaping the distribution Neanderthal at this time.

In this paper we propose a hypothesis about how abiotic drivers may have shaped Neanderthals distribution that is rooted in the Grinnellian niche concept (Grinnell 1917), the hierarchical framework proposed by Pearson et al. (2003), and our current knowledge on the ecology of Neanderthals. According to Pearson et al. (2003), climate influences species distribution at global and continental scales, while the effect of topography is restricted to scales ranging from regional to local. Our hypothesis consist of three main points: 1) the northern edge of the Neanderthals range was limited by low winter temperatures; 2) the southern edge was shaped by a combination of high temperature and low water availability during the summer; 3) high topographic diversity combined with moderate slopes could have favored occupation at the local scale. Winter temperatures at the northern edge could have resulted in a lower availability of small and big game than in temperate areas (Badgley 2000), compromising the high caloric intake required by this species (Steegmann 2002, Sørensen 2009), and an increased cold stress accelerated by a low-caloric diet, that would have lead to reduced fertility (Bocquet-Appel 2013) and a higher mortality rate (Steegmann 2002). Summer temperatures linked to continentality and the higher solar radiation of lower latitudes could have prevented the occupation of southern plains in the Mediterranean peninsulas due to increased heat stress, specially considering the low body surface area/volume ratio of this species (Churchill 2006), which hampers heat dissipation. Also, high evapotranspiration could have reduced the diversity of plants, since under-storey and forest communities are less common under such climatic conditions, hampering the access to plant resources, and making these areas unsuitable during the warm season. Mediterranean coastal areas could have been suitable because of the buffering effect of the sea over temperature and the permanent availability of resources like shellfish (Hardy 2011). At the local scale, high topographic diversity, which fosters biodiversity by an increased availability of ecological niches (Tews 2003), could have provided the required abundance and diversity of prey and shelter (Daujeard 2012), but moderate to low slopes may have been important to reduce the high energetic expenditure of mobility in steep terrain. This limitation, combined with the lower abundance of animals at higher elevations (Brown 2001), could have prevented Neanderthal’s presence in the higher elevations of the European mountain ranges.

To test our hypothesis, we have modeled and analyzed the distribution of Neanderthals during the full Eemian Interglacial (MIS 5e, $$\sim$$130 ka BP) using a PDSM approach (Franklin 2015, Svenning 2011, Varela 2011). PSDMs rely on the same principles of species distribution modeling (Guisan 2000, Guisan 2005), requiring presence coordinates coming from fossil/archaeological remains, a set of predictors (usually palaeo-climatic simulations), and an algorithm to define the relationship between presence and predictors. The result of a PSDM can be defined as a habitat suitability map in which each cell is scored according to how well it resembles the ecological conditions of the localities where the species occurs (Soberon 2005). PSDMs can be used to analyze the influence of particular drivers over the species distribution and gain ecological knowledge, as in Varela et al. (2009) or Rodríguez-Sánchez et al. (2008). PSDMs have been used before to study the distribution of Neanderthals and anatomically modern humans (Banks 2008, Banks 2008a, Beeton 2013, Burke 2014), but in this paper we add to the previous studies by offering a novel insight into the drivers of Neanderthals distribution both at continental and local scales.

We selected the Eemian Interglacial (MIS 5e, $$\sim$$130 ka BP) as modeling period for three different reasons: 1) the distribution of Neanderthals during this period has been previously assessed by i.e. Richter (2005), Richter (2006), Wenzel (2007), and Gaudzinski-Windheuser et al. (2011), providing a good baseline knowledge, but with these studies mainly focus on the core and northern edge of the distribution area across central Europe, and lack a quantitative description of Neanderthals distribution and its limiting factors; 2) since the publication of Wenzel (2007), new Neanderthal remains attributed to the Eemian have been found in Spain (Arsuaga 2012), Italy (Fiorenza 2015), France (Moncel 2007, Daujeard 2010), and these new sites have the potential to change our view about the Eemian distribution of Neanderthals; 3) During the Eemian, the warmer climatic conditions freed Europe from the Saalian ice sheet, offering the Neanderthals a unique opportunity to spread throughout Europe for c. 10000 years, and probably allowing them to reach their maximum range size. The Eemian can therefore be considered the most suitable period to assume a pseudo-equilibrium with climate for Neanderthals distribution, a key assumption for PSDMs (Guisan 2005, Guisan 2000).

In summary, in this paper we propose a hypothesis about how abiotic drivers (climate and topography) could have shaped Neanderthals distribution throughout Europe, and we test it by fitting and analyzing a PSDM describing their distribution during the Last Interglacial period.