The Role of Climate Change in Early Human Behavioural Evolution

人们普遍认为，所有物种的长期进化都受到气候和环境条件的影响。在人类进化史的大部分时间里，人们对这些因素的理解相对较差，部分原因是缺乏综合。生态位模型（ENM）为考古学家提供了一种方法来生成全球、大陆和区域尺度的人类生态位开发预测模型，为主要的进化趋势提供了广泛的背景，并将来自考古遗址的不同数据综合到一个有凝聚力的框架中。这项研究将在非洲和欧亚大陆建立早期人类居住的模型，重点关注中更新世人类进化和气候变化的关键时期。中更新世包含了人类行为和生物学的定义变化，这些变化支撑了后来智人的出现，包括；技术革新，反复使用火，延长儿童学习时间，大脑体积增大，向高纬度地区扩展。这是一个重大的气候剧变时期，通过ENM，这项研究将检验气候变化、栖息地变化和人类反应之间的相关性，提高我们对中更新世气候变化对我们进化的影响的理解。虽然enm已经在生物科学中建立起来，但它们在考古数据中的应用需要进一步的探索和改进，以更好地理解模型中固有的不确定性，以及对解释范围的影响。本研究将考察时间不确定性带来的挑战，并探索在这些延长的时间跨度中，增加模型复杂性如何影响可靠性。

It is widely recognised that all long-term species evolution is influenced by climatic and environmental conditions. These factors are relatively poorly understood for much of human evolutionary history, partly due to a lack of synthesis. Ecological Niche Modelling (ENM) offers archaeologists a method to generate global, continental and regional scale predictive models of human niche exploitation, providing the broad context for major evolutionary trends and synthesising disparate data from archaeological sites into a cohesive framework. This research will build models of early human occupation across Africa and Eurasia, focusing on a key period of human evolution and climate change within the Middle Pleistocene. The Middle Pleistocene encompasses defining changes in human behaviour and biology underpinning the later emergence of Homo sapiens including; technological innovations, repeated use of fire, extended childhood learning, increases in brain size and expansion in to higher latitudes. This follows a period of significant climatic upheaval, and through ENM this research will examine correlations between climate change, habitat change, and human responses, improving our understanding of the impact of Middle Pleistocene climate change on our evolution. Although ENMs have become established in the biological sciences, their application to archaeological data requires further exploration and refinement to better understand the inherent uncertainty in the models with implications for the scope of interpretations. This research will examine the challenges raised by chronological uncertainty, and explore how increasing model complexity may affect reliability in these extended time-spans.