Department of Anthropology, University of Utah, Salt Lake City, Utah, USA.
Am J Hum Biol. 2021 Jul;33(4):e23524. doi: 10.1002/ajhb.23524. Epub 2020 Oct 26.
Human responses to climate variation have a rich anthropological history. However, much less is known about how people living in small-scale societies perceive climate change, and what climate data are useful in predicting food production at a scale that affects daily lives.
We use longitudinal ethnographic interviews and economic data to first ask what aspects of climate variation affect the agricultural cycle and food production for Yucatec Maya farmers. Sixty years of high-resolution meteorological data and harvest assessments are then used to detect the scale at which climate data predict good and bad crop yields, and to analyze long-term changes in climate variables critical to food production.
We find that (a) only local, daily precipitation closely fits the climate pattern described by farmers. Other temporal (annual and monthly) scales miss key information about what farmers find important to successful harvests; (b) at both community- and municipal-levels, heavy late-season rains associated with tropical storms have the greatest negative impact on crop yields; and (c) in contrast to long-term patterns from regional and state data, local measures show an increase in rainfall during the late growing season, indicating that fine-grained data are needed to make accurate inferences about climate trends.
Our findings highlight the importance to define climate variables at scales appropriate to human behavior. Course-grained annual, monthly, national, and state-level data tell us little about climate attributes pertinent to farmers and food production. However, high-resolution daily, local precipitation data do capture how climate variation shapes food production.
人类对气候变化的反应在人类学历史上有着丰富的记载。然而，人们对于生活在小规模社会中的人们如何感知气候变化，以及哪些气候数据有助于预测影响日常生活的粮食产量，了解甚少。
我们采用纵向民族志访谈和经济数据，首先询问哪些方面的气候变化会影响尤卡坦玛雅农民的农业周期和粮食生产。然后，利用 60 年的高分辨率气象数据和收获评估，来检测气候数据在多大程度上可以预测粮食的好收成和坏收成，并分析对粮食生产至关重要的长期气候变化变量。
我们发现：(a)只有当地的日降水量与农民所描述的气候模式非常吻合。其他时间尺度（年和月）则错过了农民认为对成功收获至关重要的关键信息；(b)在社区和市级层面上，与热带风暴相关的后期大雨对作物产量的负面影响最大；(c)与来自地区和州数据的长期模式相反，当地措施显示出后期生长季节降雨量增加，这表明需要更精细的粒度数据来对气候趋势做出准确推断。
我们的研究结果强调了在适合人类行为的尺度上定义气候变量的重要性。粗糙的年度、月度、国家和州级数据几乎不能说明与农民和粮食生产有关的气候属性。然而，高分辨率的每日、当地降水数据确实可以捕捉到气候变化如何塑造粮食生产。
