Geography is not destiny: A quantitative test of Diamond's axis of orientation hypothesis

Abstract

Jared Diamond suggested that the unique East-West orientation of Eurasia facilitated the spread of cultural innovations and gave it substantial political, technological and military advantages over other continental regions. This controversial hypothesis assumes that innovations can spread more easily across similar habitats, and that environments tend to be more homogeneous at similar latitudes. The resulting prediction is that Eurasia is home to environmentally homogenous corridors that enable fast cultural transmission. Despite indirect evidence supporting Diamond's influential hypothesis, quantitative tests of its underlying assumptions are currently lacking. Here we address this critical gap by leveraging ecological, cultural and linguistic datasets at a global scale. Our analyses show that although societies that share similar ecologies are more likely to share cultural traits, the Eurasian continent is not significantly more ecologically homogeneous than other continental regions. Our findings highlight the perils of single factor explanations and remind us that even the most compelling ideas must be thoroughly tested to gain a solid understanding of the complex history of our species.

Keywords: Axis of orientation hypothesis; cultural biogeography; cultural evolution.

Graphical abstract

Figure 1.

General workflow for testing the (a) ecological and (b) geographic premises of Diamond's hypothesis. A global principal component analysis (PCA) at 0.5 × 0.5° resolution is first used to derive variation in temperature harshness (TH) and aridity index (AI) around the world. These climatic variables are used to compute environmental barriers to cultural spread between pairs of societies. (a) Environmental and travel barriers, along with metrics of relatedness and cultural transmission from outside the pair (green box) are run through PCAs (one for each cultural trait) to extract five principal components (PCs, burgundy box). These PCs are then used as independent variables in 54 separate models predicting the odds of sharing key cultural practices between societies in pairs (one model for each cultural trait; blue box). (b) Environmental and travel costs associated with cultural spread out of the location of each society in an agricultural centre of origin are run through two separate PCAs to cover close- and long- range spatial scales (green to burgundy boxes). We then extract three close-range (cr) and four long-range (lr) PCs as estimates of environmental barriers and use them as response variables in seven separate models (i.e. a model for each PC; blue box). In all models, the independent factor is a categorical variable showing the membership of societies to various areas of agricultural origin.

Figure 2.

Example of (a) topographic, (b) temperature, and (c) aridity least-cost paths between the locations of two societies (starting point is marked by a star). Dark colours on the cost maps indicate cells of high cost – i.e. high elevation (a) or high differences in temperature harshness (b) and aridity index (c) as compared with the starting point. Environmental heterogeneity along the least-cost path connecting two societies in a pair is estimated as the log value of accumulated cost and log value of path length.

Figure 3.

Estimated effects of principal components representing environmental and travel costs to cultural similarity. Each point denotes an independent model. The points’ values represent the estimated effect of the principal component associated with the environmental barriers listed on the y-axis label; arrows denote the size of standard errors. Models are binned into broad cultural trait categories (1–8) according to their corresponding response variables. If environmental dissimilarities are associated with a lowered potential for cultural similarity, we expect to see negative values for estimated effects. Non-significant relationships are depicted in grey, whereas significant effects are shown in red (positive) and blue (negative). The p-values are adjusted for false discovery rates.

Figure 4.

Mean and standard deviation of principal components representing environmental costs to cultural transmission in 16 known areas of domestication origin (1, South Tropical China; 2, Lower-Middle Yangtze; 3, Chinese loess plateau; 4, West Yunan and East Tibet; 5, Fertile Crescent; 6, Sava West India; 7, Ganges of East India; 8, West Africa; 9, West African Savannah; 10, Sudanic Savannah; 11, Ethiopian plateau; 12, Northern Lowlands of South America; 13, Central/Southern Andes; 14, Southwest Amazon; 15, Mesoamerica; 16, East North America). Each graph represents a separate model, where the response variable is a principal component capturing variation in the environmental barriers listed on the y-axis label. Colours highlight different major landmasses (see inset map). Panels show the comparison of environmental barriers at (a) close- and (b) long-range spatial scales. Inset matrices show pairwise Tukey's honest significant differences, with stronger blue hues depicting higher magnitudes of difference. Non-significant differences are shown in grey. Following Diamond's hypothesis, we expect smaller means for environmental costs to cultural transmission in Eurasian areas compared with other areas of the globe.