Growth rings across the Tree of Life: demographic insights from biogenic time series data

M. Evans, B. Black, D. Falk, C. L. Giebink, Emily L. Schultz
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引用次数: 1

Abstract

Biogenic time series data can be generated in a single sampling effort, offering an appealing alternative to the slow process of revisiting or recapturing individuals to measure demographic rates. Annual growth rings formed by trees and in the ear bones of fish (i.e. otoliths) are prime examples of such biogenic time series. They offer insight into not only the process of growth but also birth, death, movement, and evolution, sometimes at uniquely deep temporal and large spatial scales, well beyond 5–30 years of data collected in localised study areas. This chapter first reviews the fundamentals of how tree-ring and otolith time series data are developed and analysed (i.e. dendrochronology and sclerochronology), then surveys growth rings in other organisms, along with microstructural or microcompositional variation in growth rings, and other records of demographic processes. It highlights the answers to demographic questions revealed by these time series data, such as the influence of environmental (atmospheric or ocean) conditions, competition, and disturbances on demographic processes, and the genetic versus plastic basis of individual growth and traits that influence growth. Lastly, it considers how spatial networks of biogenic, annually resolved time series data can offer insights into the importance of macrosystem atmospheric and ocean dynamics on multispecies, trophic dynamics. The authors encourage demographers to integrate the complementary information contained in biogenic time series data into population models to better understand the drivers of vital rate variation and predict the impacts of global change.
跨越生命之树的年轮:来自生物时间序列数据的人口统计学见解
生物源时间序列数据可以在一次采样工作中生成,为重新访问或重新捕获个人以测量人口统计率的缓慢过程提供了一个有吸引力的替代方案。由树木和鱼耳骨(即耳石)形成的年轮是这种生物成因时间序列的主要例子。它们不仅提供了对生长过程的洞察,还提供了对出生、死亡、运动和进化的洞察,有时在独特的深时间和大空间尺度上,远远超出了在局部研究区域收集的5-30年的数据。本章首先回顾了如何开发和分析树木年轮和耳石时间序列数据的基本原理(即树木年代学和石器年代学),然后调查了其他生物的生长年轮,以及生长年轮的微观结构或微成分变化,以及人口统计学过程的其他记录。它强调了这些时间序列数据揭示的人口统计学问题的答案,例如环境(大气或海洋)条件、竞争和对人口统计学过程的干扰的影响,以及影响生长的个体生长和性状的遗传与可塑性基础。最后,它考虑了生物成因的空间网络,每年解决的时间序列数据如何能够提供关于大系统大气和海洋动力学对多物种营养动力学的重要性的见解。作者鼓励人口统计学家将生物成因时间序列数据中包含的补充信息整合到人口模型中,以更好地理解生命速率变化的驱动因素,并预测全球变化的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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