DOI: 10.5061/dryad.884r935
title: Data from: The global geography of human subsistence

description: How humans obtain food has dramatically reshaped ecosystems and altered
 both the trajectory of human history and the characteristics of human
 societies. Our species’ subsistence varies widely, from predominantly
 foraging strategies, to plant-based agriculture and animal husbandry. The
 extent to which environmental, social, and historical factors have driven
 such variation is currently unclear. Prior attempts to resolve
 long-standing debates on this topic have been hampered by an over-reliance
 on narrative arguments, small and geographically-narrow samples, and by
 contradictory findings. Here we overcome these methodological limitations
 by applying multi-model inference tools developed in biogeography to a
 global data set (818 societies). Although some have argued that unique
 conditions and events determine each society’s particular subsistence
 strategy, we find strong support for a general global pattern in which a
 limited set of environmental, social, and historical factors predicts an
 essential characteristic of all human groups: how we obtain our food.
description: Data associated with
 Geography of Subistence. Gavin et al. ROSWe acquired all data
 from D-PLACE (www.d-place.org). We only used data collected in a
 relatively narrow time span (1860-1960) to avoid the effects of changing
 environmental and social conditions, including long-term transitions in
 subsistence strategies, as well as the possibility that over the course of
 human history multiple groups may have occupied a given location.
 Variables describing subsistence economy (EA001 to EA005) were used to
 determine the dominant subsistence strategy, which we defined as the
 strategy relied on for more than 56% of total subsistence. We summed the
 hunting (EA002), gathering (EA001) and fishing (EA003) categories to
 represent dependence on the foraging subsistence strategy. We omitted from
 our analyses societies for which multiple strategies (foraging, animal
 husbandry, or plant-based agriculture) contributed equally, with no one
 strategy contributing more than 56%. Climate data were from the baseline
 historical (1900-1949) CCSM ecoClimate model (www.ecoclimate.org). We
 derived topographic data (slope and elevation) from the Global
 Multi-resolution Terrain Elevation Data 2010 (see ref 60 in Gavin et al
 paper). We extracted all climatic and topographic variables for the
 localities of the societies in our sample based on global maps at a 0.5 by
 0.5 degree resolution. To avoid multi-collinearity in our explanatory
 models, we reduced these often highly correlated environmental predictors
 to orthogonal components via principal components analysis (PCA). The PCA
 produced 3 main composite variables: (1) 'environmental
 stability' describes a gradient of increasing mean temperature,
 temperature predictability, mean precipitation, lower precipitation
 variance, and decreasing temperature variance; (2) 'topographic
 complexity' describes a gradient of increasing slope and elevation;
 and (3) 'environmental productivity' describes a gradient of
 increasing mean precipitation, lower precipitation variance, precipitation
 predictability, and net primary productivity. To capture the potential
 effects of horizontal transmission, we included as a predictor the
 proportion of the 10 nearest neighboring societies that share a
 society's subsistence strategy ('neighbor
 effect').Gavin et al.
 RSOS2018.datafile.xlsx