Saturday, March 24, 2018

Ecological niche models of human land use in Pleistocene Southeast Asia must account for both overall climate and environmentally specific variables

Alexandra J Zachwieja and Laura L. Shackleford
AAPA 2018, Meeting Program Abstracts
April 11-14, 2018
http://physanth.org/annual-meetings/annual-meeting-2018/

Abtract

Ecological niche models (ENM) have long been used to predict species distributions in the biological
sciences. However, their use in paleoanthropological reconstructions of hominin niches is relatively recent and has focused largely on out of Africa dispersals and human occupation in Europe and Central Asia. These studies have shown that the most important variables to predict human land use are moderate temperature, rainfall, and access to fresh water. We apply these predictors to both mainland and island Southeast Asian landscapes during the harsh climate fluctuations of the Last Glacial Maximum (LGM). We validate our ENM using known fossil human occupation sites (n=20) to construct potential human land use maps in an area where glacial climate likely influenced human diet, mobility within habitats, and dispersal to new environments. We compare human land-use outputs from two popular ENM programs, Genetic Algorithm for Rule-Set Production (GARP) and Maximum Entropy Modeling (MaxEnt), to determine which program is more beneficial for studying human land use and dispersal across time and geography. Using only these parameters, both models suggest much of Southeast Asia was amenable to human use during the LGM.

However, other environmental variables, particularly vegetation type, are likely necessary to fully understand past human land use. Rainforest environments have been considered patchier food sources than savannah environments in modern populations, and both environments were widespread in this time and place. We suggest further analysis accounting for additional environmental variables is necessary to gain a full understanding of human land use in Pleistocene Southeast Asia.

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