Doctoral Dissertation Research: Use of Tree-Ring Data to Reconstruct and Predict Maple Syrup Production in New York

枫树汁液和糖浆生产在美国东北部是一个重要的经济和文化产业，这种对温度敏感的汁液的商业收获已经发生了几个世纪。自1960年以来，枫糖浆产量的显著下降与关键制糖期春季气温上升和夏季干旱频率增加有关，但目前这种下降如何在包括枫糖浆在内的许多农产品预期的自然变异性范围内进行比较尚不清楚。缺乏综合气候学、树木生理学、森林生态学和树木年代学来调查和量化与枫糖浆生产相关的环境变量的整体研究。美国东北部的糖枫年轮年表很少，但对糖枫树轮数据的初步研究表明，该物种很容易交叉定年，树轮宽度的变化与枫糖糖浆产量显著相关。这一博士论文研究项目将结合树状年代学技术来开发产量重建以及在制糖季节前几个月预测产量。树木年轮数据的使用将允许预测不同气候条件下的枫糖浆产量。该项目将利用树轮数据将枫糖浆产量的历史记录延长100多年，从而将当前的下降置于比目前存在的更大的历史视角中。树轮数据将被用来测试在制糖季节前几个月制定准确预测的可行性，因为目前还没有预测枫糖浆产量的预测指标。这个项目将有助于确定使用糖枫树轮数据预测和重建过去两个世纪枫糖糖浆产量的有效性。它将模拟自20世纪初以来影响糖浆产量和年轮生长的气候和气象变量；它将探索20世纪50年代后糖浆产量下降的可能原因。该项目将有助于提高利用年轮数据预测农业产量的有效性，这最终将为农民提供有关作物产量周期的额外信息，这些知识将有助于在气候条件不太有利的情况下为甘蔗种植者确定适当的管理方法。这项研究的数据将发表在同行评议的期刊上，并与美国农业部、北美枫糖浆委员会、纽约州枫树生产者协会、康奈尔糖枫研究和推广计划以及国际树轮数据库共享。对于许多物种来说，高质量的长期作物产量数据是稀缺的，使用树轮数据来重建产量可能是一种可行的方法，可以扩展历史记录来研究每年到十年的收成波动。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。

Maple sap and syrup production is an economically and culturally important industry in the northeastern U.S., with commercial harvest of the temperature-sensitive sap having occurred for several centuries. Since 1960, a significant decline in maple syrup yield has been associated with warming spring temperatures during the critical sugaring period and increases in summer drought frequencies, but how this current decline compares within the natural range of variability expected for many agricultural products, including maple syrup, is unknown. Holistic studies integrating climatology, tree physiology, forest ecology, and dendrochronology to investigate and quantify the environmental variables associated with maple syrup production are lacking. Few sugar maple tree-ring chronologies from the northeastern U.S. exist, yet preliminary work with sugar maple tree-ring data indicates this species can be easily cross-dated and that variations in tree-ring widths are significantly correlated with maple syrup yield. This doctoral dissertation research project will incorporate dendrochronological techniques to develop yield reconstructions as well as predict yield up to several months prior to the sugaring season. The use of tree-ring data will allow for the forecasting of maple syrup production under different climate conditions. This project will extend the historical record of maple syrup yield by over 100 years using tree-ring data and thus place the current decline in a larger historical perspective than currently exists. The tree-ring data will be used to test the viability of developing an accurate forecast several months prior to the sugaring season, because no predictive metric currently exists to forecast maple syrup yield.This project will help determine the effectiveness of using sugar maple tree-ring data to predict and reconstruct maple syrup yields during the past two centuries. It will model climatological and meteorological variables that have affected syrup yields and tree-ring growth since the early 1900s; and it will explore the possible causes for the post-1950s decline in syrup production. The project will help promote the effectiveness of using tree-ring data to predict agricultural yields, which will ultimately provide farmers additional information about crop-yield cycles, and this knowledge will help determine appropriate management methods for sugarbush operators during less-favorable climatological conditions. The data from this research will be published in peer-reviewed journals and shared with the U.S. Department of Agriculture, the North American Maple Syrup Council, the New York State Maple Producers Associations, Inc., the Cornell Sugar Maple Research and Extension Program, and the International Tree-Ring Data Bank. High-quality, long-term crop yield data are scarce for many species, and the use of tree-ring data to reconstruct yield may be a viable method for extending historical records to examine annual-to-decadal harvest fluctuations. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.